Long-term and multimodal memory for AI agents - character-aware, mem0-compatible, fully-local option
Telemem is an MCP integration. Long-term and multimodal memory for AI agents - character-aware, mem0-compatible, fully-local option.
The published pypi package is telemem, version 1.10.0. Its declared MCP transport is stdio.
The package declares OPENAI_API_KEY: API key for the default OpenAI LLM/embedder (not needed with a local TELEMEM_CONFIG); TELEMEM_CONFIG: Path to a TeleMem YAML/JSON config, e.g. the fully-local Ollama + FAISS setup (config/config.ollama.yaml); TELEMEM_DEFAULT_USER_ID: Default memory scope when tool calls omit user_id/agent_id/run_id (default: telemem-mcp).
Check the maintainer’s instructions for account access, authentication and the supported client configuration. Once connected, inspect the tools your client receives and try a small task that matches the server’s stated purpose. The registry description does not include a verified, complete tool list.
View the publisher’s registry entry · Project repository. This profile uses version 1.10.0 from the registry. Registration identifies the publisher namespace; it does not establish that this is a first-party integration for every service it connects.
Browse related developer tools MCP servers for tools that cover the same kind of work.
| Variable | Description | Required |
|---|---|---|
| OPENAI_API_KEY | API key for the default OpenAI LLM/embedder (not needed with a local TELEMEM_CONFIG) | Optional |
| TELEMEM_CONFIG | Path to a TeleMem YAML/JSON config, e.g. the fully-local Ollama + FAISS setup (config/config.ollama.yaml) | Optional |
| TELEMEM_DEFAULT_USER_ID | Default memory scope when tool calls omit user_id/agent_id/run_id (default: telemem-mcp) | Optional |
Store entities, relations and observations in a local knowledge graph with the reference Memory MCP server.
A structured scratchpad for hard problems — stepwise reasoning with revisions, branches and visible logic.
DASH Research Vault MCP server — local-first semantic search, note persistence, and public-safe knowledge-base tools for MCP-compatible agents.
Long-term memory for AI coding agents: durable project facts, recalled by every MCP client.
Authority-weighted memory graph for AI agents with conflict detection and semantic search.
Academic paper knowledge-base MCP server: PDF ingest, vector search with reranking, KB management.