What does the Cognify_and_search tool do?
It constructs a knowledge graph from the provided text and then performs a search using the given query, returning the matching edges of the graph.
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Builds knowledge graph from the input text and performs search in it.
An MCP server for cognee, an AI memory engine. It provides a tool that builds a knowledge graph from input text and performs search within that graph, returning retrieved edges.
Configure it in your Claude Desktop client (claude_desktop_config.json) using uvx. Set the required environment variables (e.g., LLM_API_KEY, GRAPH_DATABASE_PROVIDER, VECTOR_DB_PROVIDER, DB_PROVIDER, DB_NAME). Invoke the Cognify_and_search tool with the text and search query as inputs.
It constructs a knowledge graph from the provided text and then performs a search using the given query, returning the matching edges of the graph.
Yes. You can optionally provide a `graph_model_file` (filename of a custom Pydantic graph model implementation) and `graph_model_name` (the class name) to customize the graph structure.
You must set `LLM_API_KEY`, `GRAPH_DATABASE_PROVIDER`, `VECTOR_DB_PROVIDER`, `DB_PROVIDER`, and `DB_NAME`. Example values: networkx, lancedb, sqlite.
It requires Python and uv (for running via uvx). The optional custom graph model feature depends on a Pydantic implementation.
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