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projectmind MCP server

by Nodemint-dev·io.github.Nodemint-dev/projectmind·v0.6.0·2 stars
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Persistent project memory for AI coding agents: one compact digest instead of re-reading the repo.

A85/100grade A
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Safety scan
A85/100

full report

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2 stars

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

projectmind tools (7, 1 write)

write = sends, deletes, buys or posts

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

  • mind_context

    Call this BEFORE reading/greping files, when you're about to work on specific files or a module and want its purpose, notes, and direct dependencies without opening them. Given the files you're about to edit (and/or a node id or keyword), returns ONLY the relevant part of the map. Use this over mind_digest when you already know which files a task touches — it's the most surgical, token-cheap optio

  • mind_digest

    Call this BEFORE running ls, find, glob, grep, tree, or reading any file, whenever the task is to explain, describe, summarize, or give an overview of this project or its architecture, or when you otherwise need to orient yourself in an unfamiliar codebase. This includes questions like "what is this project", "explain this codebase", "what's the tech stack", or "how is this structured" — call mind

  • mind_handoff

    Leave a one-line handoff note — what you were doing and what's next — before the session ends or the context is about to be compacted. It appears at the TOP of the next session's mind_digest, so the next session (yours or a teammate's agent) resumes instantly instead of rediscovering the task. Stored in the developer's local overlay, never committed. Pass clear: true when the noted work is done.

  • mind_query

    Get full detail on ONE node (its files, notes, and edges) when you need to drill into a specific module. Use after mind_digest points you at the right node — cheaper than reading the files.

  • mind_search

    Find nodes, decisions, or glossary terms by keyword. Use to locate the right part of the project without reading files.

  • mind_stats

    Return map size, the estimated token cost of the digest, and the local savings ledger (estimated tokens/dollars saved by reading the map instead of scanning files).

  • mind_updatewrite action

    Call this when you add or change a module, make an architectural decision, or learn a project convention — so the next session doesn't have to rediscover it. Do NOT call for trivial edits. Pass ONLY the fields that changed.

Public scan report

scanner v0.1.9 · 2026-09-26 · same rubric, same numbers if you re-run it

no findings
  • Code scan9 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 82 days ago12/15
  • Maintainer identityregistry namespace matches repository owner6/10
Overall 85/100. Components that don't apply are left out of the denominator. Any critical finding is an F.RubricAppeal a findingJSON

How projectmind compares

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

Safety score
85/100
higher than 70% of 48,255 servers
Tools
7
the typical server has 7
Tools that change things
14%
typical: 0%. Fewer write tools means less an agent can break
GitHub stars
2
more than 75% of 28,688 servers

What its tools let an agent do: 6 read · 1 change

Install projectmind in Claude Code, Cursor or VS Code

Runs npx -y @nodemint/projectmind on your machine. Read the scan report first; the gateway never runs local packages.

claude mcp add projectmind -- npx -y @nodemint/projectmind
Add to Cursor

What the publisher says

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

projectmind

Persistent, compact project memory for AI coding agents. Your agent reads one small digest instead of re-scanning the codebase every session — and a local ledger shows you exactly how many tokens (and dollars) that saved.

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Every AI coding session starts the same way: the agent has no memory of your project, so it re-reads files, re-derives your architecture, or asks you to re-explain decisions you made months ago. You pay for that in tokens, time, and wrong guesses — every single session, on every machine, for every teammate.

projectmind fixes this with a structured, persistent project map (.projectmind/map.json): your modules, their dependencies, your architectural decisions, your conventions, your domain glossary. The agent reads a ~400-token digest first, drills into single nodes only when needed, and writes back what it learns — so the next session (yours, a teammate's, or a different AI tool's) starts already knowing the project.

The digest scales with your project's conceptual size (modules, decisions), not its byte size — so the savings grow with the repo.

Quick start — one command

npm install -g @nodemint/projectmind
cd your-repo
projectmind init

That single init does everything: scaffolds the map, seeds it from your repo layout, detects which AI agents are installed on your machine and wires each one (MCP server + a rules file carrying the live map), adds .projectmind/ to your .gitignore (the map stays local — nothing to push), and installs the git hook that keeps the map fresh on every commit.

Then the one step no tool can do for you: restart your agent (or start a new chat session). AI agents load their config and rules files at session start — a chat that was already open keeps its old context, and every session after that has the map automatically. Using the VS Code savings extension? Cmd+Shift+P → "Developer: Reload Window" once.

Want it available in every future project without even running init?

projectmind setup --global        # registers the MCP server once, user-wide

(projectmind init --bare scaffolds only, and projectmind setup re-wires agents on demand, if you prefer the pieces separately.)

See what it saves you — measured, not promised

The MCP server keeps a local savings ledger: every time your agent reads the map instead of scanning files, it records the tokens actually served vs. the estimated tokens of the files the agent would have read instead.

Check it anytime:

$ projectmind savings
projectmind savings (estimated — local ledger, never leaves this machine)

  Total saved:   ~20.5k tokens across 22 map read(s)
  ≈ $0.0614 at sonnet-tier input pricing ($3/MTok, as of 2026-06)
  Today:         ~20.5k tokens (22 read(s))

Shortened. The full README is on GitHub.

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

projectmind: common questions

Is projectmind MCP server safe?
Yes, by our scan: it is graded A (85/100). Read the projectmind safety report
How do I install projectmind?
It runs on your machine. Copy the Claude Code, Cursor, VS Code or Claude Desktop config from the install section.
Does projectmind need an API key?
Not as far as the registry entry and our scan can tell: no credentials are declared or required.
Is projectmind maintained?
The last commit was 121 days ago (2026-07-06). The latest release is v0.6.0.
What can I use instead of projectmind?
Servers from other publishers that do the same job: Deja Vu MCP server, Memorix MCP server and State Memory MCP server.
How does projectmind compare with other MCP servers?
safety score 85/100 (higher than 70% of 48,255 servers); tools 7 (the typical server has 7); tools that change things 14% (typical: 0%. Fewer write tools means less an agent can break). Full comparison.

Alternatives to projectmind

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

  • Deja Vu
    deja-vu: local memory over the session histories of forty-three coding agents.
    A
  • Memorix
    Local-first project memory with legacy MCP and 2026 discovery compatibility.
    B
  • State Memory MCP
    Persistent workflow graph server tracking tasks, decisions, spatial entities, and blockers.
    A
  • Knowl
    Persistent memory for AI agents, for code, research and everyday life. Stale facts retire.
    A