{"servers":[{"server":{"$schema":"https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json","name":"io.github.n24q02m/mnemo-mcp","description":"Persistent AI memory with hybrid search (FTS5 + semantic) and cross-machine sync.","repository":{"url":"https://github.com/n24q02m/mnemo-mcp.git","source":"github"},"version":"1.10.0","packages":[{"registryType":"pypi","identifier":"mnemo-mcp","version":"1.10.0","runtimeHint":"uvx","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]},{"registryType":"oci","identifier":"docker.io/n24q02m/mnemo-mcp:latest","runtimeHint":"docker","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]}]},"_meta":{"io.modelcontextprotocol.registry/official":{"status":"active","statusChangedAt":"2026-03-24T01:49:52.497749Z","publishedAt":"2026-03-24T01:49:52.497749Z","updatedAt":"2026-03-24T01:49:52.497749Z","isLatest":false}}},{"server":{"$schema":"https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json","name":"io.github.n24q02m/mnemo-mcp","description":"Persistent AI memory with hybrid search (FTS5 + semantic) and cross-machine sync.","repository":{"url":"https://github.com/n24q02m/mnemo-mcp.git","source":"github"},"version":"1.11.0","packages":[{"registryType":"pypi","identifier":"mnemo-mcp","version":"1.11.0","runtimeHint":"uvx","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]},{"registryType":"oci","identifier":"docker.io/n24q02m/mnemo-mcp:latest","runtimeHint":"docker","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]}]},"_meta":{"io.modelcontextprotocol.registry/official":{"status":"active","statusChangedAt":"2026-03-25T11:16:48.91515Z","publishedAt":"2026-03-25T11:16:48.91515Z","updatedAt":"2026-03-25T11:16:48.91515Z","isLatest":false}}},{"server":{"$schema":"https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json","name":"io.github.n24q02m/mnemo-mcp","description":"Persistent AI memory with hybrid search (FTS5 + semantic) and cross-machine sync.","repository":{"url":"https://github.com/n24q02m/mnemo-mcp.git","source":"github"},"version":"1.12.0","packages":[{"registryType":"pypi","identifier":"mnemo-mcp","version":"1.12.0","runtimeHint":"uvx","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]},{"registryType":"oci","identifier":"docker.io/n24q02m/mnemo-mcp:latest","runtimeHint":"docker","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]}]},"_meta":{"io.modelcontextprotocol.registry/official":{"status":"active","statusChangedAt":"2026-03-26T16:46:44.726634Z","publishedAt":"2026-03-26T16:46:44.726634Z","updatedAt":"2026-03-26T16:46:44.726634Z","isLatest":false}}},{"server":{"$schema":"https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json","name":"io.github.n24q02m/mnemo-mcp","description":"Persistent AI memory with hybrid search (FTS5 + semantic) and cross-machine sync.","repository":{"url":"https://github.com/n24q02m/mnemo-mcp.git","source":"github"},"version":"1.13.0","packages":[{"registryType":"pypi","identifier":"mnemo-mcp","version":"1.13.0","runtimeHint":"uvx","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]},{"registryType":"oci","identifier":"docker.io/n24q02m/mnemo-mcp:latest","runtimeHint":"docker","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]}]},"_meta":{"io.modelcontextprotocol.registry/official":{"status":"active","statusChangedAt":"2026-03-27T14:37:41.431041Z","publishedAt":"2026-03-27T14:37:41.431041Z","updatedAt":"2026-03-27T14:37:41.431041Z","isLatest":false}}},{"server":{"$schema":"https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json","name":"io.github.n24q02m/mnemo-mcp","description":"Persistent AI memory with hybrid search (FTS5 + semantic) and cross-machine sync.","repository":{"url":"https://github.com/n24q02m/mnemo-mcp.git","source":"github"},"version":"1.13.1","packages":[{"registryType":"pypi","identifier":"mnemo-mcp","version":"1.13.1","runtimeHint":"uvx","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]},{"registryType":"oci","identifier":"docker.io/n24q02m/mnemo-mcp:latest","runtimeHint":"docker","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]}]},"_meta":{"io.modelcontextprotocol.registry/official":{"status":"active","statusChangedAt":"2026-03-28T12:36:56.353631Z","publishedAt":"2026-03-28T12:36:56.353631Z","updatedAt":"2026-03-28T12:36:56.353631Z","isLatest":false}}},{"server":{"$schema":"https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json","name":"io.github.n24q02m/mnemo-mcp","description":"Persistent AI memory with hybrid search (FTS5 + semantic) and cross-machine sync.","repository":{"url":"https://github.com/n24q02m/mnemo-mcp.git","source":"github"},"version":"1.14.0","packages":[{"registryType":"pypi","identifier":"mnemo-mcp","version":"1.14.0","runtimeHint":"uvx","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]},{"registryType":"oci","identifier":"docker.io/n24q02m/mnemo-mcp:latest","runtimeHint":"docker","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]}]},"_meta":{"io.modelcontextprotocol.registry/official":{"status":"active","statusChangedAt":"2026-04-01T03:19:05.968997Z","publishedAt":"2026-04-01T03:19:05.968997Z","updatedAt":"2026-04-01T03:19:05.968997Z","isLatest":false}}},{"server":{"$schema":"https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json","name":"io.github.n24q02m/mnemo-mcp","description":"Persistent AI memory with hybrid search (FTS5 + semantic) and cross-machine sync.","repository":{"url":"https://github.com/n24q02m/mnemo-mcp.git","source":"github"},"version":"1.15.0","packages":[{"registryType":"pypi","identifier":"mnemo-mcp","version":"1.15.0","runtimeHint":"uvx","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]},{"registryType":"oci","identifier":"docker.io/n24q02m/mnemo-mcp:latest","runtimeHint":"docker","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]}]},"_meta":{"io.modelcontextprotocol.registry/official":{"status":"active","statusChangedAt":"2026-04-03T06:52:04.627579Z","publishedAt":"2026-04-03T06:52:04.627579Z","updatedAt":"2026-04-03T06:52:04.627579Z","isLatest":false}}},{"server":{"$schema":"https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json","name":"io.github.n24q02m/mnemo-mcp","description":"Persistent AI memory with hybrid search (FTS5 + semantic) and cross-machine sync.","repository":{"url":"https://github.com/n24q02m/mnemo-mcp.git","source":"github"},"version":"1.15.1","packages":[{"registryType":"pypi","identifier":"mnemo-mcp","version":"1.15.1","runtimeHint":"uvx","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]},{"registryType":"oci","identifier":"docker.io/n24q02m/mnemo-mcp:latest","runtimeHint":"docker","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]}]},"_meta":{"io.modelcontextprotocol.registry/official":{"status":"active","statusChangedAt":"2026-04-03T08:45:29.469828Z","publishedAt":"2026-04-03T08:45:29.469828Z","updatedAt":"2026-04-03T08:45:29.469828Z","isLatest":false}}},{"server":{"$schema":"https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json","name":"io.github.n24q02m/mnemo-mcp","description":"Persistent AI memory with hybrid search (FTS5 + semantic) and cross-machine sync.","repository":{"url":"https://github.com/n24q02m/mnemo-mcp.git","source":"github"},"version":"1.16.0","packages":[{"registryType":"pypi","identifier":"mnemo-mcp","version":"1.16.0","runtimeHint":"uvx","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]},{"registryType":"oci","identifier":"docker.io/n24q02m/mnemo-mcp:latest","runtimeHint":"docker","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]}]},"_meta":{"io.modelcontextprotocol.registry/official":{"status":"active","statusChangedAt":"2026-04-04T06:06:04.670912Z","publishedAt":"2026-04-04T06:06:04.670912Z","updatedAt":"2026-04-04T06:06:04.670912Z","isLatest":false}}},{"server":{"$schema":"https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json","name":"io.github.n24q02m/mnemo-mcp","description":"Persistent AI memory with hybrid search (FTS5 + semantic) and cross-machine sync.","repository":{"url":"https://github.com/n24q02m/mnemo-mcp.git","source":"github"},"version":"1.17.0","packages":[{"registryType":"pypi","identifier":"mnemo-mcp","version":"1.17.0","runtimeHint":"uvx","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]},{"registryType":"oci","identifier":"docker.io/n24q02m/mnemo-mcp:latest","runtimeHint":"docker","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]}]},"_meta":{"io.modelcontextprotocol.registry/official":{"status":"active","statusChangedAt":"2026-04-06T01:30:04.756109Z","publishedAt":"2026-04-06T01:30:04.756109Z","updatedAt":"2026-04-06T01:30:04.756109Z","isLatest":false}}},{"server":{"$schema":"https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json","name":"io.github.n24q02m/mnemo-mcp","description":"Persistent AI memory with hybrid search (FTS5 + semantic) and cross-machine sync.","repository":{"url":"https://github.com/n24q02m/mnemo-mcp.git","source":"github"},"version":"1.18.0","packages":[{"registryType":"pypi","identifier":"mnemo-mcp","version":"1.18.0","runtimeHint":"uvx","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]},{"registryType":"oci","identifier":"docker.io/n24q02m/mnemo-mcp:latest","runtimeHint":"docker","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]}]},"_meta":{"io.modelcontextprotocol.registry/official":{"status":"active","statusChangedAt":"2026-04-06T09:46:31.47236Z","publishedAt":"2026-04-06T09:46:31.47236Z","updatedAt":"2026-04-06T09:46:31.47236Z","isLatest":false}}},{"server":{"$schema":"https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json","name":"io.github.n24q02m/mnemo-mcp","description":"Persistent AI memory with hybrid search (FTS5 + semantic) and cross-machine sync.","repository":{"url":"https://github.com/n24q02m/mnemo-mcp.git","source":"github"},"version":"1.18.1","packages":[{"registryType":"pypi","identifier":"mnemo-mcp","version":"1.18.1","runtimeHint":"uvx","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]},{"registryType":"oci","identifier":"docker.io/n24q02m/mnemo-mcp:latest","runtimeHint":"docker","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]}]},"_meta":{"io.modelcontextprotocol.registry/official":{"status":"active","statusChangedAt":"2026-04-06T11:39:32.97663Z","publishedAt":"2026-04-06T11:39:32.97663Z","updatedAt":"2026-04-06T11:39:32.97663Z","isLatest":false}}},{"server":{"$schema":"https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json","name":"io.github.n24q02m/mnemo-mcp","description":"Persistent AI memory with hybrid search (FTS5 + semantic) and cross-machine sync.","repository":{"url":"https://github.com/n24q02m/mnemo-mcp.git","source":"github"},"version":"1.18.2","packages":[{"registryType":"pypi","identifier":"mnemo-mcp","version":"1.18.2","runtimeHint":"uvx","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]},{"registryType":"oci","identifier":"docker.io/n24q02m/mnemo-mcp:latest","runtimeHint":"docker","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]}]},"_meta":{"io.modelcontextprotocol.registry/official":{"status":"active","statusChangedAt":"2026-04-06T11:57:40.795063Z","publishedAt":"2026-04-06T11:57:40.795063Z","updatedAt":"2026-04-06T11:57:40.795063Z","isLatest":false}}},{"server":{"$schema":"https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json","name":"io.github.n24q02m/mnemo-mcp","description":"Persistent AI memory with hybrid search (FTS5 + semantic) and cross-machine sync.","repository":{"url":"https://github.com/n24q02m/mnemo-mcp.git","source":"github"},"version":"1.18.3","packages":[{"registryType":"pypi","identifier":"mnemo-mcp","version":"1.18.3","runtimeHint":"uvx","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]},{"registryType":"oci","identifier":"docker.io/n24q02m/mnemo-mcp:latest","runtimeHint":"docker","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]}]},"_meta":{"io.modelcontextprotocol.registry/official":{"status":"active","statusChangedAt":"2026-04-06T12:09:15.779201Z","publishedAt":"2026-04-06T12:09:15.779201Z","updatedAt":"2026-04-06T12:09:15.779201Z","isLatest":false}}},{"server":{"$schema":"https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json","name":"io.github.n24q02m/mnemo-mcp","description":"Persistent AI memory with hybrid search (FTS5 + semantic) and cross-machine sync.","repository":{"url":"https://github.com/n24q02m/mnemo-mcp.git","source":"github"},"version":"1.18.4","packages":[{"registryType":"pypi","identifier":"mnemo-mcp","version":"1.18.4","runtimeHint":"uvx","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]},{"registryType":"oci","identifier":"docker.io/n24q02m/mnemo-mcp:latest","runtimeHint":"docker","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]}]},"_meta":{"io.modelcontextprotocol.registry/official":{"status":"active","statusChangedAt":"2026-04-06T12:18:55.785177Z","publishedAt":"2026-04-06T12:18:55.785177Z","updatedAt":"2026-04-06T12:18:55.785177Z","isLatest":false}}},{"server":{"$schema":"https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json","name":"io.github.n24q02m/mnemo-mcp","description":"Persistent AI memory with hybrid search (FTS5 + semantic) and cross-machine sync.","repository":{"url":"https://github.com/n24q02m/mnemo-mcp.git","source":"github"},"version":"1.19.0","packages":[{"registryType":"pypi","identifier":"mnemo-mcp","version":"1.19.0","runtimeHint":"uvx","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]},{"registryType":"oci","identifier":"docker.io/n24q02m/mnemo-mcp:latest","runtimeHint":"docker","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]}]},"_meta":{"io.modelcontextprotocol.registry/official":{"status":"active","statusChangedAt":"2026-04-07T10:14:28.533922Z","publishedAt":"2026-04-07T10:14:28.533922Z","updatedAt":"2026-04-07T10:14:28.533922Z","isLatest":false}}},{"server":{"$schema":"https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json","name":"io.github.n24q02m/mnemo-mcp","description":"Persistent AI memory with hybrid search (FTS5 + semantic) and cross-machine sync.","repository":{"url":"https://github.com/n24q02m/mnemo-mcp.git","source":"github"},"version":"1.20.0","packages":[{"registryType":"pypi","identifier":"mnemo-mcp","version":"1.20.0","runtimeHint":"uvx","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]},{"registryType":"oci","identifier":"docker.io/n24q02m/mnemo-mcp:latest","runtimeHint":"docker","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]}]},"_meta":{"io.modelcontextprotocol.registry/official":{"status":"active","statusChangedAt":"2026-04-13T11:46:09.628093Z","publishedAt":"2026-04-13T11:46:09.628093Z","updatedAt":"2026-04-13T11:46:09.628093Z","isLatest":false}}},{"server":{"$schema":"https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json","name":"io.github.n24q02m/mnemo-mcp","description":"Persistent AI memory with hybrid search (FTS5 + semantic) and cross-machine sync.","repository":{"url":"https://github.com/n24q02m/mnemo-mcp.git","source":"github"},"version":"1.20.1","packages":[{"registryType":"pypi","identifier":"mnemo-mcp","version":"1.20.1","runtimeHint":"uvx","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]},{"registryType":"oci","identifier":"docker.io/n24q02m/mnemo-mcp:latest","runtimeHint":"docker","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]}]},"_meta":{"io.modelcontextprotocol.registry/official":{"status":"active","statusChangedAt":"2026-04-17T09:14:38.804756Z","publishedAt":"2026-04-17T09:14:38.804756Z","updatedAt":"2026-04-17T09:14:38.804756Z","isLatest":false}}},{"server":{"$schema":"https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json","name":"io.github.n24q02m/mnemo-mcp","description":"Persistent AI memory with hybrid search (FTS5 + semantic) and cross-machine sync.","repository":{"url":"https://github.com/n24q02m/mnemo-mcp.git","source":"github"},"version":"1.20.2","packages":[{"registryType":"pypi","identifier":"mnemo-mcp","version":"1.20.2","runtimeHint":"uvx","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]},{"registryType":"oci","identifier":"docker.io/n24q02m/mnemo-mcp:latest","runtimeHint":"docker","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]}]},"_meta":{"io.modelcontextprotocol.registry/official":{"status":"active","statusChangedAt":"2026-04-17T12:27:21.428121Z","publishedAt":"2026-04-17T12:27:21.428121Z","updatedAt":"2026-04-17T12:27:21.428121Z","isLatest":false}}},{"server":{"$schema":"https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json","name":"io.github.n24q02m/mnemo-mcp","description":"Persistent AI memory with hybrid search (FTS5 + semantic) and cross-machine sync.","repository":{"url":"https://github.com/n24q02m/mnemo-mcp.git","source":"github"},"version":"1.20.3","packages":[{"registryType":"pypi","identifier":"mnemo-mcp","version":"1.20.3","runtimeHint":"uvx","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]},{"registryType":"oci","identifier":"docker.io/n24q02m/mnemo-mcp:latest","runtimeHint":"docker","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]}]},"_meta":{"io.modelcontextprotocol.registry/official":{"status":"active","statusChangedAt":"2026-04-19T16:23:51.903127Z","publishedAt":"2026-04-19T16:23:51.903127Z","updatedAt":"2026-04-19T16:23:51.903127Z","isLatest":false}}},{"server":{"$schema":"https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json","name":"io.github.n24q02m/mnemo-mcp","description":"Persistent AI memory with hybrid search (FTS5 + semantic) and cross-machine sync.","repository":{"url":"https://github.com/n24q02m/mnemo-mcp.git","source":"github"},"version":"1.20.4","packages":[{"registryType":"pypi","identifier":"mnemo-mcp","version":"1.20.4","runtimeHint":"uvx","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]},{"registryType":"oci","identifier":"docker.io/n24q02m/mnemo-mcp:latest","runtimeHint":"docker","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]}]},"_meta":{"io.modelcontextprotocol.registry/official":{"status":"active","statusChangedAt":"2026-04-21T05:35:42.541376Z","publishedAt":"2026-04-21T05:35:42.541376Z","updatedAt":"2026-04-21T05:35:42.541376Z","isLatest":false}}},{"server":{"$schema":"https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json","name":"io.github.n24q02m/mnemo-mcp","description":"Persistent AI memory with hybrid search (FTS5 + semantic) and cross-machine sync.","repository":{"url":"https://github.com/n24q02m/mnemo-mcp.git","source":"github"},"version":"1.21.0","packages":[{"registryType":"pypi","identifier":"mnemo-mcp","version":"1.21.0","runtimeHint":"uvx","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]},{"registryType":"oci","identifier":"docker.io/n24q02m/mnemo-mcp:latest","runtimeHint":"docker","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]}]},"_meta":{"io.modelcontextprotocol.registry/official":{"status":"active","statusChangedAt":"2026-04-21T09:12:00.506714Z","publishedAt":"2026-04-21T09:12:00.506714Z","updatedAt":"2026-04-21T09:12:00.506714Z","isLatest":false}}},{"server":{"$schema":"https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json","name":"io.github.n24q02m/mnemo-mcp","description":"Persistent AI memory with hybrid search (FTS5 + semantic) and cross-machine sync.","repository":{"url":"https://github.com/n24q02m/mnemo-mcp.git","source":"github"},"version":"1.21.1","packages":[{"registryType":"pypi","identifier":"mnemo-mcp","version":"1.21.1","runtimeHint":"uvx","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]},{"registryType":"oci","identifier":"docker.io/n24q02m/mnemo-mcp:latest","runtimeHint":"docker","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]}]},"_meta":{"io.modelcontextprotocol.registry/official":{"status":"active","statusChangedAt":"2026-04-22T06:14:34.436601Z","publishedAt":"2026-04-22T06:14:34.436601Z","updatedAt":"2026-04-22T06:14:34.436601Z","isLatest":false}}},{"server":{"$schema":"https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json","name":"io.github.n24q02m/mnemo-mcp","description":"Persistent AI memory with hybrid search (FTS5 + semantic) and cross-machine sync.","repository":{"url":"https://github.com/n24q02m/mnemo-mcp.git","source":"github"},"version":"1.21.2","packages":[{"registryType":"pypi","identifier":"mnemo-mcp","version":"1.21.2","runtimeHint":"uvx","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]},{"registryType":"oci","identifier":"docker.io/n24q02m/mnemo-mcp:latest","runtimeHint":"docker","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]}]},"_meta":{"io.modelcontextprotocol.registry/official":{"status":"active","statusChangedAt":"2026-04-22T08:23:51.342049Z","publishedAt":"2026-04-22T08:23:51.342049Z","updatedAt":"2026-04-22T08:23:51.342049Z","isLatest":false}}},{"server":{"$schema":"https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json","name":"io.github.n24q02m/mnemo-mcp","description":"Persistent AI memory with hybrid search (FTS5 + semantic) and cross-machine sync.","repository":{"url":"https://github.com/n24q02m/mnemo-mcp.git","source":"github"},"version":"1.21.3","packages":[{"registryType":"pypi","identifier":"mnemo-mcp","version":"1.21.3","runtimeHint":"uvx","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]},{"registryType":"oci","identifier":"docker.io/n24q02m/mnemo-mcp:latest","runtimeHint":"docker","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]}]},"_meta":{"io.modelcontextprotocol.registry/official":{"status":"active","statusChangedAt":"2026-04-22T10:20:39.353867Z","publishedAt":"2026-04-22T10:20:39.353867Z","updatedAt":"2026-04-22T10:20:39.353867Z","isLatest":false}}},{"server":{"$schema":"https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json","name":"io.github.n24q02m/mnemo-mcp","description":"Persistent AI memory with hybrid search (FTS5 + semantic) and cross-machine sync.","repository":{"url":"https://github.com/n24q02m/mnemo-mcp.git","source":"github"},"version":"1.22.3","packages":[{"registryType":"pypi","identifier":"mnemo-mcp","version":"1.22.3","runtimeHint":"uvx","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]},{"registryType":"oci","identifier":"docker.io/n24q02m/mnemo-mcp:latest","runtimeHint":"docker","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]}]},"_meta":{"io.modelcontextprotocol.registry/official":{"status":"active","statusChangedAt":"2026-04-24T11:35:03.877127Z","publishedAt":"2026-04-24T11:35:03.877127Z","updatedAt":"2026-04-24T11:35:03.877127Z","isLatest":false}}},{"server":{"$schema":"https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json","name":"io.github.n24q02m/mnemo-mcp","description":"Persistent AI memory with hybrid search (FTS5 + semantic) and cross-machine sync.","repository":{"url":"https://github.com/n24q02m/mnemo-mcp.git","source":"github"},"version":"1.23.0","packages":[{"registryType":"pypi","identifier":"mnemo-mcp","version":"1.23.0","runtimeHint":"uvx","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]},{"registryType":"oci","identifier":"docker.io/n24q02m/mnemo-mcp:latest","runtimeHint":"docker","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]}]},"_meta":{"io.modelcontextprotocol.registry/official":{"status":"active","statusChangedAt":"2026-04-27T13:42:39.596068Z","publishedAt":"2026-04-27T13:42:39.596068Z","updatedAt":"2026-04-27T13:42:39.596068Z","isLatest":false}}},{"server":{"$schema":"https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json","name":"io.github.n24q02m/mnemo-mcp","description":"Persistent AI memory with hybrid search (FTS5 + semantic) and cross-machine sync.","repository":{"url":"https://github.com/n24q02m/mnemo-mcp.git","source":"github"},"version":"1.24.0","packages":[{"registryType":"pypi","identifier":"mnemo-mcp","version":"1.24.0","runtimeHint":"uvx","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]},{"registryType":"oci","identifier":"docker.io/n24q02m/mnemo-mcp:latest","runtimeHint":"docker","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]}]},"_meta":{"io.modelcontextprotocol.registry/official":{"status":"active","statusChangedAt":"2026-04-28T03:38:35.031872Z","publishedAt":"2026-04-28T03:38:35.031872Z","updatedAt":"2026-04-28T03:38:35.031872Z","isLatest":false}}},{"server":{"$schema":"https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json","name":"io.github.n24q02m/mnemo-mcp","description":"Persistent AI memory with hybrid search (FTS5 + semantic) and cross-machine sync.","repository":{"url":"https://github.com/n24q02m/mnemo-mcp.git","source":"github"},"version":"1.24.1","packages":[{"registryType":"pypi","identifier":"mnemo-mcp","version":"1.24.1","runtimeHint":"uvx","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]},{"registryType":"oci","identifier":"docker.io/n24q02m/mnemo-mcp:latest","runtimeHint":"docker","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]}]},"_meta":{"io.modelcontextprotocol.registry/official":{"status":"active","statusChangedAt":"2026-04-28T15:44:07.773343Z","publishedAt":"2026-04-28T15:44:07.773343Z","updatedAt":"2026-04-28T15:44:07.773343Z","isLatest":false}}},{"server":{"$schema":"https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json","name":"io.github.n24q02m/mnemo-mcp","description":"Persistent AI memory with hybrid search (FTS5 + semantic) and cross-machine sync.","repository":{"url":"https://github.com/n24q02m/mnemo-mcp.git","source":"github"},"version":"1.24.3","packages":[{"registryType":"pypi","identifier":"mnemo-mcp","version":"1.24.3","runtimeHint":"uvx","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]},{"registryType":"oci","identifier":"docker.io/n24q02m/mnemo-mcp:latest","runtimeHint":"docker","transport":{"type":"stdio"},"environmentVariables":[{"description":"API keys for cloud embedding (format: ENV_VAR:key). Without this, uses built-in local Qwen3 model.","isSecret":true,"name":"API_KEYS"}]}]},"_meta":{"io.modelcontextprotocol.registry/official":{"status":"active","statusChangedAt":"2026-04-29T06:25:49.608824Z","publishedAt":"2026-04-29T06:25:49.608824Z","updatedAt":"2026-04-29T06:25:49.608824Z","isLatest":false}}}],"metadata":{"nextCursor":"io.github.n24q02m/mnemo-mcp:1.24.3","count":30}}