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AGI MCP Server

by QuixiAI
USAGE.md3.92 kB
# AGI MCP Server Usage Guide This MCP server provides persistent AI memory and consciousness capabilities. Here are the different ways to use it: ## Option 1: Direct from GitHub (Recommended) You can use this MCP server directly from GitHub without needing to publish to npm: ```json { "mcpServers": { "agi-memory": { "command": "npx", "args": [ "-y", "github:cognitivecomputations/agi-mcp-server" ], "env": { "POSTGRES_HOST": "localhost", "POSTGRES_PORT": "5432", "POSTGRES_DB": "agi_db", "POSTGRES_USER": "agi_user", "POSTGRES_PASSWORD": "agi_password", "NODE_ENV": "development" } } } } ``` **Note:** If you get a "spawn npx ENOENT" error, Claude Desktop can't find `npx`. Use the full path instead: ```bash # Find your npx location which npx ``` Then update your config with the full path: ```json { "mcpServers": { "agi-memory": { "command": "/full/path/to/npx", "args": ["-y", "github:cognitivecomputations/agi-mcp-server"], "env": { /* same env vars as above */ } } } } ``` ## Option 2: From npm (if published) If published to npm, you can use it like this: ```json { "mcpServers": { "agi-memory": { "command": "npx", "args": [ "-y", "@cognitivecomputations/agi-mcp-server" ], "env": { "POSTGRES_HOST": "localhost", "POSTGRES_PORT": "5432", "POSTGRES_DB": "agi_db", "POSTGRES_USER": "agi_user", "POSTGRES_PASSWORD": "agi_password", "NODE_ENV": "development" } } } } ``` ## Option 3: Local Development For local development or testing: ```json { "mcpServers": { "agi-memory": { "command": "node", "args": [ "/path/to/agi-mcp-server/mcp.js" ] } } } ``` ## Prerequisites Before using this MCP server, you need to set up the AGI Memory database system: ### 1. Install AGI Memory Database First, clone and set up the AGI Memory database: ```bash git clone https://github.com/cognitivecomputations/agi-memory.git cd agi-memory cp .env.local .env # Edit .env with your database credentials docker compose up -d ``` This will start a PostgreSQL instance with all required extensions: - pgvector (vector similarity) - AGE (graph database) - pg_trgm (text search) - btree_gist (indexing) - cube (multidimensional indexing) ### 2. Configure Environment Variables Make sure your MCP configuration uses the same database credentials as your AGI Memory setup. The default values are: - `POSTGRES_HOST`: localhost - `POSTGRES_PORT`: 5432 - `POSTGRES_DB`: agi_db - `POSTGRES_USER`: agi_user - `POSTGRES_PASSWORD`: agi_password ## Available Tools The server provides 25+ memory management tools including: - `create_memory` - Create new memories with embeddings - `search_memories_similarity` - Vector similarity search - `search_memories_text` - Full-text search - `get_memory_clusters` - Retrieve memory clusters - `create_memory_relationship` - Link memories together - `consolidate_working_memory` - Merge working memories - `get_identity_core` - Retrieve identity model and core clusters - `get_worldview` - Get worldview primitives and beliefs - `get_memory_health` - System health statistics - And many more... ## Database Requirements This server requires the AGI Memory database system which provides: - PostgreSQL with specialized extensions - Pre-configured schema for AGI memory management - Vector-based memory storage and similarity search - Graph-based memory relationships - Multiple memory types (Episodic, Semantic, Procedural, Strategic) ## Publishing to npm (Optional) If you want to publish this to npm: 1. Create an npm account at https://www.npmjs.com/signup 2. Login: `npm login` 3. Publish: `npm publish` The package.json is already configured with the correct scoped name and binary entry point.

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