Tokenmizer MCP server

TokenMizer

Your AI forgets why. TokenMizer remembers.

An OpenAI-compatible proxy that builds a knowledge graph of your session — decisions, files, errors, goals — and replays it when the context window runs out. Not a summary: a queryable graph that knows "we switched from MongoDB to PostgreSQL, and here is why."

One line to adopt · works with Claude, GPT, Gemini, Grok, DeepSeek, Mistral, Cohere, Ollama · MIT

Quick start · See it · Claude Code & MCP · Benchmarks · Architecture · Roadmap

Real run: 25-node graph, checkpoint ckpt21a0959c3ddf, 233-token resume. Regenerate with python scripts/gendemo_gif.py.

The problem

Every AI session has a context limit. When you hit it, the model forgets every decision and every rationale built over hours of work, and you spend the first ten minutes of the next session re-explaining the project.

Summarising the history does not fix this. A summary tells you what was decided; it loses why, and it loses what was rejected — so the model happily re-proposes the thing you moved off three sessions ago.

Quick start

pip install "tokenmizer[anthropic,cache]"
export TOKENMIZER_ANTHROPIC_API_KEY=sk-ant-...
tokenmizer serve

Then change one line in your client:

from openai import OpenAI

client = OpenAI(
    api_key="your-key",
    base_url="http://localhost:8000/v1",   # only this changes
)

Shortened. The full README is on GitHub.