a-mem-mcp-server
by saurabhmain
Overview
An agentic memory system for LLM agents, enhancing research by storing, linking, and evolving knowledge based on the Zettelkasten principle, with IDE integration.
Installation
python -m src.a_mem.mainEnvironment Variables
- LLM_PROVIDER
- OLLAMA_BASE_URL
- OLLAMA_LLM_MODEL
- OLLAMA_EMBEDDING_MODEL
- OPENROUTER_API_KEY
- OPENROUTER_BASE_URL
- OPENROUTER_LLM_MODEL
- OPENROUTER_EMBEDDING_MODEL
- TCP_SERVER_ENABLED
- TCP_SERVER_HOST
- TCP_SERVER_PORT
- RESEARCHER_ENABLED
- RESEARCHER_CONFIDENCE_THRESHOLD
- RESEARCHER_MAX_SOURCES
- RESEARCHER_MAX_CONTENT_LENGTH
- JINA_READER_ENABLED
- JINA_READER_HOST
- JINA_READER_PORT
- UNSTRUCTURED_ENABLED
- UNSTRUCTURED_API_URL
- UNSTRUCTURED_API_KEY
- UNSTRUCTURED_USE_LIBRARY
- GOOGLE_SEARCH_ENABLED
- GOOGLE_API_KEY
- GOOGLE_SEARCH_ENGINE_ID
- GRAPH_BACKEND
Security Notes
The server exposes a `/get_graph` endpoint via an `aiohttp` web server, by default on `127.0.0.1:42424`, which is read-only but exposes internal graph data. The `add_file` tool processes file paths provided by the user/agent; if a malicious actor controls this input, it could potentially be used to read arbitrary files accessible to the server process, leading to information disclosure. Additionally, public Google API keys are hardcoded as defaults, which, while likely for a public Custom Search Engine, is still poor practice and could lead to API quota exhaustion.
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