Tinycontext MCP server

TinyContext

<!-- mcp-name: io.github.TinySuiteHQ/tinycontext -->

Context that fits your local LLMs.

TinyContext is a token-light local memory layer for AI agents. It stores concise memories and their embeddings in SQLite, ranks them with hybrid BM25 and dense retrieval, and returns only the context that fits the requested token budget.

No hosted account. No giant context dumps. No required vector database.

Choose a tier

The Python library contains the memory engine. MCP, FastAPI, and Docker are adapters around the same savememories, recallmemories, and delete_memory operations.

One-command MCP

Add TinyContext to any stdio MCP client:

{
  "mcpServers": {
    "tinycontext": {
      "command": "uvx",
      "args": [
        "--python",
        "3.12",
        "--from",
        "tinysuite-context[server]",
        "tinycontext"
      ]
    }
  }
}

The no-argument tinycontext command runs stdio MCP. On its first launch, TinyContext downloads the selected ONNX embedding bundle into its per-user data directory. The database is created lazily on the first save or recall. Later launches reuse both local assets.

Check the resolved configuration and storage readiness with:

uvx --python 3.12 --from "tinysuite-context[server]" tinycontext doctor

TinyContext exposes six tools:

save_memories(memories)
recall_memories(query=None, top_k=None)
list_memories(kind=None, since=None, until=None, limit=None, offset=0)
get_memory(memory_id)
update_memory(memory_id, content)
delete_memory(memory_id)

Shortened. The full README is on GitHub.