hermes-labs-ai/fidelis

**Your agent can forget a summary. Fidelis brings back the note.**
Local memory for Codex, Claude Code, and other agents: save text across sessions and retrieve the original passage when it matters.
by Hermes Labs
PyPI · Connect an agent · Technical reference
A project summary might say “billing migration rolled back.” The original note says **why** it failed and **do not retry until the idempotency fix is verified**. When your next session depends on that condition, the missing sentence matters.
Fidelis stores your Markdown and text notes and retrieves their stored wording. Its default retrieval does not ask a generative model to rewrite your memory.
Try it with one note
This path supports Python 3.10+, macOS or Ubuntu, and a local Ollama service. Start Ollama if needed (ollama serve in a separate terminal). No model API key is required. The current release is **0.3.0rc1**.
bash
fidelis mcp install --client codex
Or, for Claude Code:
fidelis mcp install
Restart the client and try: **“Use Fidelis to find my Atlas billing migration note. What must happen before we retry? Quote the relevant text.”**
The client gets tools to recall, store, correct, fetch, and inspect memory. It decides when to call them; installing the connection does not make every turn recall automatically. Other clients and uninstall commands include Cursor, Gemini CLI, Copilot CLI, and OpenClaw. A separate Pi extension provides prompt-time recall.
What Fidelis preserves
- **Original wording.** watch, store, and other verbatim write paths keep the text you supplied, so retrieval can return the condition that a summary might omit.
- **Local retrieval.** Fast vector search is the default MCP recall path. Explicit hybrid search combines keyword and vector results without a generative LLM at its zero_llm` tier; local embeddings still require Ollama.
- **Corrections over time.** A correction can supersede a prior record without erasing it. Recall can show validity and historical status instead of silently replacing the old note.
Fidelis also has optional extraction and model-assisted routes. Those can transform or filter inputs; use the verbatim path when the original wording is the point. Retrieved text can still be wrong or out of date, and your agent's model provider may see it when answering.