MCP.Market

crewlore MCP server

by srijansk·io.github.srijansk/crewlore·v0.5.3

Team knowledge compiled from your coding agents' sessions and pull requests, every entry cited.

A92/100grade A
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Safety scan
A92/100

full report

Adoption
Growing

0 stars363 downloads/wk

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If you have run it, two minutes of your experience saves the next person an afternoon.

crewlore tools (3)

write = sends, deletes, buys or posts

Read from the package source without running it. The installed server may list more.

  • lore_explain

    Everything known about one scope: current practice first, then declined work, each with its anchors, plus the live conflicts recorded for the scope.

  • lore_feedback

    Record what became of returned claims: verdict is "influential", "overridden" or "corrected".

  • lore_query

    Return team-knowledge claims relevant to a task, each with verbatim anchors.

Public scan report

scanner v0.1.10 · 2026-10-25 · same rubric, same numbers if you re-run it

no findings
  • Code scan35 source files scanned25/25
  • –Live reliabilityno gateway calls yet and no remote to proben/a
  • –Tool poisoningtools not inspected (local package is not executed); not countedn/a
  • Auth qualitylocal package, no credentials required12/15
  • Maintenancelast push 2 days ago15/15
  • Maintainer identityregistry namespace matches repository owner; GitHub account older than a year8/10
Overall 92/100. Components that don't apply are left out of the denominator. Any critical finding is an F.RubricAppeal a findingJSON

How crewlore compares

Against every graded MCP server, from our own scans and uptime checks. Updated after each scan run.

Safety score
92/100
higher than 95% of 48,255 servers
Tools
3
the typical server has 7
Tools that change things
0%
typical: 0%. Fewer write tools means less an agent can break
Downloads a week
363
more than 84% of 12,191 servers with a package

What its tools let an agent do: 3 read

Install crewlore in Claude Code, Cursor or VS Code

claude mcp add crewlore -- uvx crewlore
Add to Cursor

What the publisher says

From the crewlore repository's README, as published. We do not edit it. Read it on GitHub

Your coding agents keep relearning what your team already figured out.

crewlore reads the sessions your agents already produce, and your repo's pull requests, pulls out the decisions, procedures and gotchas, and writes them into a plain-text knowledge book inside your repo. Every entry quotes the exact line it came from, and records whether the team adopted it or tried it and declined. Runs on your machine with your own model key.

Sixty seconds on what it does and how it is used:

https://github.com/user-attachments/assets/b16cb272-da48-4756-89ba-1cc626629e0c

The same thing in a terminal. The recording below is the bundled demo, uv run python scripts/demo.py --step, which needs no API key: a handful of synthetic sessions compiled into a book, including one claim the team tried and declined.

pipx install crewlore

You need: Python 3.10 or newer; a model key (ANTHROPICAPIKEY or OPENAIAPIKEY) or a local OpenAI-compatible model; the GitHub CLI (gh auth login) if you want to compile pull requests; uv only for the no-key demo below.

Quickstart

Two ways in, depending on where your team's knowledge currently lives.

You already use Claude Code. Point lore at the transcripts it writes to disk. By default it reads only this repo's own transcripts, never the other projects on your machine.

cd my-repo
export ANTHROPIC_API_KEY=...     # or OPENAI_API_KEY, or a local model in .lore/config.yaml
lore init                        # create .lore/ in your repo
lore watch                       # read this repo's transcripts, scrub secrets, compile, prune — on an interval
lore query "billing webhook"     # ask the knowledge layer anything, anytime

You have a repo but no sessions yet. Compile its pull-request threads instead. Coding agents write much of their reasoning in PR descriptions and reviews — what they tried, why it failed, which constraint they hit — so a repo nobody has run an agent in locally already has a knowledge layer waiting:

cd my-repo
export ANTHROPIC_API_KEY=...
lore init
lore import-prs owner/repo       # closed PRs by default, agent-authored only; uses your gh login, stores no token
lore query "billing webhook"

Either way, commit .lore/ and your teammates inherit the book on their next git pull. Its own .gitignore keeps raw transcripts, raw PR exports, the extraction cache and usage counters out of git.

Trouble installing?

If pipx fails with Broken Python installation, platform.mac_ver() returned an empty value, your default Python is a broken install (sometimes seen with very recent Homebrew Python builds). This is about the interpreter pipx uses, not the package — pin a known-working one:

pipx install --python python3.13 crewlore

To make pipx default to Python 3.13 going forward: export PIPXDEFAULTPYTHON=$(which python3.13).

Try it without an API key

Shortened. The full README is on GitHub.

Nothing above is checked by us. What we check is on the safety report.

crewlore: common questions

Is crewlore MCP server safe?
Yes, by our scan: it is graded A (92/100). Read the crewlore safety report
How do I install crewlore?
It runs on your machine. Copy the Claude Code, Cursor, VS Code or Claude Desktop config from the install section.
Does crewlore need an API key?
Not as far as the registry entry and our scan can tell: no credentials are declared or required.
Is crewlore maintained?
The last commit was 12 days ago (2026-10-23). The latest release is v0.5.3.
What can I use instead of crewlore?
Servers from other publishers that do the same job: llmwiki MCP server and Deja Vu MCP server.
How does crewlore compare with other MCP servers?
safety score 92/100 (higher than 95% of 48,255 servers); tools 3 (the typical server has 7); tools that change things 0% (typical: 0%. Fewer write tools means less an agent can break). Full comparison.

Alternatives to crewlore

Same job from other publishers: the closest match first, then the best rated.

  • llmwiki
    Compile documents into a cited knowledge wiki. Retrieve evidence, query, and review via local MCP.
    A
  • Deja Vu
    deja-vu: local memory over the session histories of forty-three coding agents.
    A