Graqle MCP server

GraQle — give your AI a memory of how your organisation actually works

Turn the context your organisation already has — codebases, documents, policies, decisions and workflows — into a persistent typed knowledge graph, so Claude Code, Cursor, Copilot and other agents reason over architecture, dependencies, prior lessons and evidence instead of re-reading disconnected files every session.

Models change. Tools change. Your architecture and institutional knowledge should not.

pip install graqle

Website · Quickstart · How it works · Governed autonomy · Regulated deployments · Changelog · VS Code Extension

<!-- mcp-name: io.github.quantamixsol/graqle -->

Why GraQle exists

Your organisation already knows the answer. It just can't hand it to an AI.

The refund threshold lives in a policy document. The reason you retain records for seven years is in an ADR nobody re-reads. The incident that moved validation into the service layer is in someone's head. The dependency that makes payments fragile is in the code. Every one of those is real knowledge — and none of it is connected to any of the others, so no model can reason across it.

Each AI session starts from zero and rebuilds a partial picture from whatever files fit in the context window. Then the window closes and the picture is gone.

GraQle builds that connection once, keeps it, and grows it.

• Relationships, not files. Assistants see documents and files. GraQle sees how a policy, a decision and the code that implements it relate — and what breaks when one of them changes.
• Memory that compounds. Policies, decisions, lessons and architecture become durable graph nodes instead of disappearing with a chat session. Teach it once; every future session starts from there.
• Model independence. Swap models, providers or IDEs without rebuilding the intelligence layer.

90-second proof — no code required

Point GraQle at policies, ADRs, runbooks or specs. Nothing else needed — this works on a folder with no code in it at all.

pip install graqle

# 1. Turn a folder of organisational documents into a typed graph
graq scan docs ./policies
# → 3 files → 12 nodes: 3 Document + 9 Section, linked by SECTION_OF

# 2. Teach it a rule that lives in nobody's file
graq learn knowledge "vendor DPA must be signed before any data access" --domain policy
# → extracts the entity "DPA", then SEMANTICALLY_RELATED-links the rule to
#   the vendor-onboarding document AND to its "Due diligence" section

# 3. Ask across the whole body of knowledge
graq run "what approval is needed for a large refund?"
# → answer + confidence + evidence trail + the exact sections consulted

# 4. Audit what the organisation has taught it
graq learned

Shortened. The full README is on GitHub.