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The memory layer for AI coding agents. SessionFS captures every session, builds organizational knowledge, and gives your next AI agent everything the last one learned.

$ pip install sessionfs
~/ terminal
$ sfs list
Sessions (8)
ID Tool Msgs
ses_a1b2claude-code47
ses_c3d4codex31
ses_e5f6gemini23
ses_g7h8copilot15
ses_i9j0cursor52
ses_k1l2amp18
ses_m3n4cline9
ses_o5p6roo-code27
Works with
Claude CodeCodexGeminiCopilotCursorAmpClineRoo Code
GitHub stars 1,344 backend + 109 UI tests Enterprise tested
Governance

Complete audit trail of every AI action across every tool and every developer.

Onboarding

New engineers' AI tools know the codebase from day one. Zero ramp-up time.

Continuity

Context never lost between sessions, tools, or teammates. Work always resumes.

Risk Reduction

Every AI claim verified. Secrets detected before sync. Contradictions surfaced.

Your team's AI gets smarter with every session.

Every captured session is automatically distilled into knowledge entries — architecture decisions, debugging patterns, API contracts, and environment quirks. Your codebase builds its own documentation over time.

AI agents don't just read the knowledge base — they write back. When an agent discovers something new during a session, it adds the finding automatically via MCP. The next agent picks it up.

22 MCP tools Auto-compiled wiki Agent write-back
Learn more →
knowledge base
$ sfs project ask "How does auth work?"
Knowledge Base Results
auth/middleware — JWT validation via PyJWT. Tokens refreshed on 401. Middleware checks Authorization header, decodes with RS256.
auth/oauth2 — OAuth2 flow uses authorization_code grant. Callback at /auth/callback. Tokens stored in httponly cookies.
auth/testing — Test fixtures use factory_boy. Auth tokens mocked via conftest.py pytest fixtures.
Answer saved to knowledge base. ✓

Reviewable AI at scale.

Every AI coding agent makes claims: "the test passes," "I created the file," "the migration is safe." Most go unverified. LLM Judge cross-references every claim against actual evidence — exit codes, file writes, test output.

Confidence-scored findings surface on PRs and in the dashboard. Your team reviews AI work the same way they review human work.

Verified claims feed the knowledge base — building a trust record your team can reference.

BYOK — your key, never stored. Works with any OpenAI-compatible endpoint: OpenRouter, LiteLLM, vLLM, Ollama.

Read the docs →
audit report
Trust Score
74%
3 contradictions · 9 unverified · 42 verified
CRITICAL test_result
AI: "The test passes successfully"
FAILED tests/test_auth.py
assert status_code == 200, got 401
exit code: 1
HIGH file_existence
AI: "I've created validator.py"
Reality: No Write call to that path

How it works

Three commands. Under a minute. Zero behavior change.

1

Capture

$ sfs daemon start
Watching 8 tools... (PID 48201)
claude-code codex gemini
copilot cursor amp

Sessions captured from 8 tools automatically. No config needed.

2

Browse

$ sfs list
ID       Tool        Msgs
ses_a1b2 claude-code 47
ses_c3d4 codex       31
ses_e5f6 gemini      23

Browse sessions across all tools in one unified view.

3

Resume

$ sfs resume ses_d20e --in gemini
Converting claude-code -> gemini...
Session resumed. 47 messages loaded.

Resume any session in any supported tool. Full context preserved.

Everything you need

Cloud Sync

Push to the cloud, pull on any machine. Auto-sync available with three modes: off, all, or selective.

sfs sync auto --mode all

MCP Server · 12 Tools

Your AI agents read project context, search knowledge, and write discoveries back — all via MCP.

sfs mcp install --for claude-code

Session Summary

See what happened in 10 seconds. Files, tests, commands — extracted automatically with no LLM cost.

3 modified · 5/6 tests · 34 cmds

Team Handoff

Hand off sessions with full context. Session data copies to recipient automatically.

sfs handoff --to sarah@co.dev

GitHub & GitLab

AI session context on every PR and MR. Contradictions surfaced for reviewers.

Cloud + self-hosted GitLab

Self-Hosted

Deploy to any Kubernetes cluster with Helm. Your data never leaves your infrastructure.

helm install sessionfs ./charts

Your data. Your boundary.

Choose the deployment model that fits your security requirements.

Managed Single-Tenant

Dedicated infrastructure provisioned for your organization. Isolated compute, storage, and networking. We manage it — you own the data.

  • Isolated GCP project per tenant
  • SOC 2 + HIPAA ready
  • 99.9% SLA

Self-Hosted

Deploy to your own Kubernetes cluster — AWS EKS, GCP GKE, Azure AKS, or on-prem. Nothing leaves your network. Air-gapped deployment available.

  • Helm chart, enterprise-tested
  • SAML SSO + RBAC
  • Air-gapped option

Free during beta.

Local capture, cloud sync, team handoff, knowledge base, MCP, and LLM Judge — all included. No credit card required.

Paid plans with storage-based pricing are coming after beta.