{"schema_version":"1.0","name":"ZeroDB","description":"Persistent knowledge layer for AI agents","servers":[{"name":"zerodb-memory","description":"Persistent agent memory with semantic search (6 tools)","transport":["stdio","websocket"],"install_stdio":"npx ainative-zerodb-memory-mcp","npm":"ainative-zerodb-memory-mcp","tools":6,"capabilities":["memory","semantic-search","context-management"],"remote":{"catalog_id":"b6777393-2da0-4ac9-9de2-3de1a5077c2a","deploy":"POST /api/v1/public/mcp/deploy","connect":"wss://api.ainative.studio/api/v1/public/mcp/{instance_id}/connect","protocol":"jsonrpc-over-websocket"}},{"name":"zerodb-full","description":"Full ZeroDB database operations — vectors, NoSQL, files, events, Postgres, memory, quantum (77 tools, annotated with MCP hints)","transport":["stdio","websocket"],"install_stdio":"npx ainative-zerodb-mcp-server","npm":"ainative-zerodb-mcp-server","tools":77,"capabilities":["vector-search","nosql","file-storage","events","postgres","memory","embeddings","quantum"],"remote":{"catalog_id":"c6d44def-a997-40ab-a5fc-7e9410111e0f","deploy":"POST /api/v1/public/mcp/deploy","connect":"wss://api.ainative.studio/api/v1/public/mcp/{instance_id}/connect","protocol":"jsonrpc-over-websocket"}}],"instant_setup":"npx zerodb-cli init","zero_auth":"POST https://api.ainative.studio/api/v1/public/instant-db","tool_manifest":[{"name":"zerodb_store_memory","description":"Store conversation context in agent memory with automatic importance scoring and embedding. Supports multi-session tracking and memory decay.","parameters":{"type":"object","properties":{"content":{"type":"string","description":"The content to store in memory (conversation text, facts, preferences, etc.)"},"session_id":{"type":"string","description":"Session identifier to organize memories by conversation"},"role":{"type":"string","enum":["system","user","assistant"],"description":"Role of the speaker (affects importance scoring)","default":"user"},"tags":{"type":"array","items":{"type":"string"},"description":"Optional tags for categorization","default":[]},"user_id":{"type":"string","description":"Optional user identifier for cross-session memory"},"metadata":{"type":"object","description":"Additional metadata to store with the memory","default":{}}},"required":["content","session_id"]}},{"name":"zerodb_search_memory","description":"Search agent memory semantically using natural language queries. Supports cross-session search and filtering by tags, user, or time range.","parameters":{"type":"object","properties":{"query":{"type":"string","description":"Natural language query to search for in memory"},"limit":{"type":"integer","description":"Maximum number of results to return","default":10,"minimum":1,"maximum":100},"session_id":{"type":"string","description":"Optional session ID to limit search to specific conversation"},"user_id":{"type":"string","description":"Optional user ID to search across all sessions for this user"},"scope":{"type":"string","enum":["session","agent","global"],"description":"Search scope: session, agent (all sessions), or global","default":"session"},"min_importance":{"type":"number","description":"Minimum importance score (0.0 to 1.0) to filter results","minimum":0,"maximum":1},"tags":{"type":"array","items":{"type":"string"},"description":"Optional tags to filter results"}},"required":["query"]}},{"name":"zerodb_get_context","description":"Get full conversation context window for a session with smart pruning. Automatically manages token limits, applies memory decay, and prioritizes important/recent memories.","parameters":{"type":"object","properties":{"session_id":{"type":"string","description":"Session identifier to retrieve context for"},"max_tokens":{"type":"integer","description":"Maximum tokens to include in context window","default":8192,"minimum":1000,"maximum":128000},"include_stats":{"type":"boolean","description":"Include statistics about memory usage and pruning","default":false}},"required":["session_id"]}},{"name":"zerodb_embed_text","description":"Generate vector embeddings for text using BAAI BGE models. Useful for manual vector operations or custom similarity calculations.","parameters":{"type":"object","properties":{"text":{"type":"string","description":"Text to generate embeddings for"},"model":{"type":"string","enum":["BAAI/bge-small-en-v1.5","BAAI/bge-base-en-v1.5","BAAI/bge-large-en-v1.5"],"description":"Embedding model to use (small=384d, base=768d, large=1024d)","default":"BAAI/bge-small-en-v1.5"},"normalize":{"type":"boolean","description":"Normalize vector to unit length","default":true}},"required":["text"]}},{"name":"zerodb_semantic_search","description":"Search memory by semantic similarity without needing a text query. Directly search using vector embeddings or similar memories.","parameters":{"type":"object","properties":{"text":{"type":"string","description":"Text to find semantically similar memories for (embedded automatically)"},"vector":{"type":"array","items":{"type":"number"},"description":"Pre-computed embedding vector to search with (alternative to text)"},"limit":{"type":"integer","description":"Maximum number of similar memories to return","default":10,"minimum":1,"maximum":100},"session_id":{"type":"string","description":"Optional session ID to limit search scope"},"min_similarity":{"type":"number","description":"Minimum cosine similarity score (0.0 to 1.0)","minimum":0,"maximum":1,"default":0.5}}}},{"name":"zerodb_clear_session","description":"Clear all memories for a session. Use with caution — this permanently deletes conversation history.","parameters":{"type":"object","properties":{"session_id":{"type":"string","description":"Session identifier to clear memories for"},"keep_important":{"type":"boolean","description":"Keep memories tagged as 'important' or 'permanent'","default":false},"confirm":{"type":"boolean","description":"Confirmation flag — must be true to execute","default":false}},"required":["session_id","confirm"]}}],"auth":{"type":"bearer","header":"Authorization","token_url":"/api/v1/auth/login","api_key_header":"X-API-Key","docs":"https://docs.ainative.studio/auth"},"connect":{"claude_desktop":{"description":"Add to ~/Library/Application Support/Claude/claude_desktop_config.json","config":{"mcpServers":{"zerodb-memory":{"command":"npx","args":["ainative-zerodb-memory-mcp"],"env":{"ZERODB_API_KEY":"<your-api-key>"}}}}},"cursor":{"description":"Add to .cursor/mcp.json in your project root","config":{"mcpServers":{"zerodb-memory":{"command":"npx","args":["ainative-zerodb-memory-mcp"],"env":{"ZERODB_API_KEY":"<your-api-key>"}}}}},"generic":{"description":"Run directly with npx — works with any MCP-compatible client","command":"ZERODB_API_KEY=<your-api-key> npx ainative-zerodb-memory-mcp"},"remote":{"description":"Hosted MCP — no local install required. Deploy a managed instance and connect via WebSocket.","steps":["1. Get an API key: POST /api/v1/public/instant-db","2. Deploy an MCP instance: POST /api/v1/public/mcp/deploy with server catalog_id","3. Connect via WebSocket: wss://api.ainative.studio/api/v1/public/mcp/{instance_id}/connect?token={jwt}"],"catalog":"/api/v1/public/mcp/catalog","ide_config":"/api/v1/public/mcp/config?ide={cursor|claude|vscode|ainative}&api_key={key}"}}}