You never need these, but they're handy.

Want knock to ignore some files? List them in a .knockignore file (same format as .gitignore).

Commit a .mcp.json file to your repo, and every teammate's Claude Code picks up knock automatically (each person needs knock installed):

{
  "mcpServers": {
    "knock": { "command": "knock", "args": ["serve", "--repo", ".", "--toolset", "map"] }
  }
}

Each person's notes live on their own machine. Sharing findings across a team isn't supported yet (see Status below).

On Flask, an agent is told: "sessions signed with an old key in SECRET_KEY_FALLBACKS are rejected after rotating SECRET_KEY".

1. get_context returns ~7.7 KB containing:
   • src/flask/sessions.py:317: SecureCookieSessionInterface.get_signing_serializer
   • tests/test_basic.py:374: test_session_secret_key_fallbacks
   • related commits fb54159861 secret key rotation: fix key list ordering and e13373f838 enable secret key rotation
   • the docs sections on sessions and secret keys
2. get_source("src/flask/sessions.py", symbol="get_signing_serializer") returns the ~80 relevant lines, not the whole file.
3. record_knowledge saves the finding:

   {"category": "debugging",
    "content": "get_signing_serializer builds the key list as SECRET_KEY_FALLBACKS followed by SECRET_KEY; ordering was fixed in fb54159.",
    "sources": [{"path": "src/flask/sessions.py", "start_line": 317, "end_line": 335}]}
   

   The next session gets it instantly. If sessions.py changes, the note is flagged stale.

• Flask (used during development, so optimistic): knock 12/12 with 92K chars, baselines 7/12 with 2.1M and 247K chars.
• Speed: a ~200-file repo indexes in 0.3–0.6 s; re-indexing with no changes takes ~30 ms.
• What this measures: whether the facts reached the agent, not whether the agent then solved the task. The baselines are simulations of agent behaviour.
• In real Claude Code sessions (3 runs each), the result depends on the repository and the task:
  • Flask (small and well known): knock was break-even on a bug investigation and slightly more expensive on an easy edit, where its extra steps outweigh a single search.
  • Saleor (4,776 files, released days before the test), with the compact map toolset: on a multi-module investigation, knock cut the median cost from $0.49 to $0.29 and model time from 170 s to 78 s, and every knock run was cheaper. On a follow-up edit whose file one regex search found, knock cost more ($0.14 vs $0.08).
  • Latest version (adds edit mode and "skip knock for easy edits" guidance), over the full investigate-then-edit scenario: Saleor's median two-day cost fell from $0.70 to $0.43 (−39%). On Flask it was $0.31 vs $0.27, within run-to-run noise. Claude followed the guidance: it used knock for every investigation and skipped it for all the Flask edits.
  • Details and caveats are in docs/benchmark.md.
• Not yet measured: real billed tokens with a live model. The harness is ready (benchmarks/agent_bench.py) but costs API credits to run.
• Where knock missed: wording mismatches ("linters" vs "lint") and module-level variables it doesn't index yet.

Full methodology: docs/benchmark.md.

That's the goal, and the benchmark shows far less text reaching the agent. But your bill also includes system prompts, reasoning, and output, and prompt caching already discounts repeated input. Expect the biggest wins on exploration-heavy questions ("how does X work?", "where is Y?", "how do we deploy?"), and little on pure code-writing. Faster answers and memory across sessions are wins either way.

No. Indexing and search are fully deterministic and local. The only thing that uses an API is the optional benchmark.

Any agent that supports MCP over stdio. Verified: Claude Code (the session at the top of this page is a real recording of Claude using knock's tools) and the official MCP Python SDK client (all 8 tools, in the test suite). Cursor, Windsurf and others should work but are untested. Setup: docs/agents.md.

Python (deeply, via its syntax tree), plus JavaScript/TypeScript, Go, Rust, Java, Kotlin, C#, Ruby, PHP, Swift, C/C++ and more. It also reads Markdown and reStructuredText docs, ADRs, package.json, pyproject.toml, go.mod, Cargo.toml, Dockerfiles, Makefiles, GitHub Actions, linter configs and git history. Full list: docs/architecture.md.

Every note is labelled with where it came from (extracted from docs, recorded by an agent, git history) and how fresh it is. Agents can mark a note as wrong, and it stays hidden until the source changes. The real file is always one get_source away.

No embeddings and no vector database. knock stores small structured facts that point back to exact lines, tracks when those lines change, and lets agents add what they learn. It's closer to a team wiki that maintains itself than to a search index.