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MCP Server / ctx

ctx

Skill, agent, MCP and harness recommendation engine for Claude Code/custom LLMs: walks a 13,218-node LLM wiki graph (1,968 skills, 464 agents, 10,786 MCP servers, 963K edges) and suggests the right tools on the fly.

★ 262von @stevesolunMITGitHub →

Transport

sse

Dokumentation

ctx — Skill, Agent, MCP & Harness Recommendation

Watches what you develop, walks a knowledge graph of 1,968 skills, 464 agents, 10,786 MCP servers, and cataloged harnesses, and recommends the right bundle on the fly. You approve what loads, installs, or gets adopted. Powered by a Karpathy LLM wiki with persistent memory that gets smarter every session.

2026-04-27 updates.

Why it exists

  • Discovery — with 1,900+ skills, 460+ agents, 10K+ MCP servers, and cataloged harnesses, you can't possibly know which exist or which apply to your current work.
  • Context budget — loading everything wastes tokens and degrades quality. You need the right 10–15 per session.
  • Skill rot — skills you installed months ago and never used are cluttering context. Stale ones should be flagged automatically.

Install

pip install claude-ctx
ctx-init                    # terminal wizard: hooks, graph, model, harness goal
ctx-init --wizard           # force the same wizard from scripts/tests
ctx-init --model-mode skip  # non-interactive setup for automation
ctx-init --model-mode custom --model openai/gpt-5.5 --goal "build a CAD agent"

Optional extras: pip install "claude-ctx[embeddings]" for the semantic backend, pip install "claude-ctx[dev]" for the test toolchain.

Pre-built knowledge graph (optional)

A pre-built knowledge graph of 13,218 nodes and 963K edges ships as a tarball. Extract to get a ready-to-use ~/.claude/skill-wiki/:

# after `git clone` — or download graph/wiki-graph.tar.gz from the GitHub release
mkdir -p ~/.claude/skill-wiki
tar xzf graph/wiki-graph.tar.gz -C ~/.claude/skill-wiki/

Windows / Git-Bash / MSYS: pass --force-local so tar doesn't read the c: in the path as a remote host: tar --force-local xzf graph/wiki-graph.tar.gz -C ~/.claude/skill-wiki/. Linux/macOS users can ignore.

Use

After install, the ctx hooks integrate automatically with Claude Code's PostToolUse + Stop events. Typical flow:

ctx-scan-repo --repo .     # scan current repo and stack signals
ctx-scan-repo --repo . --recommend  # include skill/agent/MCP/harness recommendations
ctx-agent-add --agent-path ./code-reviewer.md --name code-reviewer
ctx-harness-add --repo https://github.com/earthtojake/text-to-cad --tag cad
ctx-harness-install text-to-cad --dry-run   # inspect before cloning/running anything
ctx-harness-install text-to-cad --update --dry-run
ctx-harness-install text-to-cad --uninstall --dry-run
ctx-skill-quality list     # four-signal quality score for every skill
ctx-skill-quality explain python-patterns   # drill into a single skill
ctx-skill-health dashboard # structural health + drift detection
ctx-toolbox run --event pre-commit          # run a council on the current diff
ctx-monitor serve          # local dashboard: http://127.0.0.1:8765/

The ctx-monitor dashboard shows currently loaded skills, agents, and MCP servers with load/unload buttons, a cytoscape graph view (/graph?slug=…), the LLM-wiki entity browser (/wiki/<slug>), a filterable skills grid, a session timeline, an audit log viewer, and a live SSE event stream. Dashboard harness exposure is not yet present; harnesses are cataloged and recommended through the CLI/API surfaces.

When ctx-skill-add, ctx-agent-add, ctx-mcp-add, or ctx-harness-add finds an existing entity, ctx prints a benefits/risks update review and skips replacement by default. Re-run with --update-existing to apply the catalog or local asset update after review.

Step-by-step entity onboarding: https://stevesolun.github.io/ctx/entity-onboarding/

Full docs, architecture, and every module: https://stevesolun.github.io/ctx/

License

MIT — see LICENSE.