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Hunch MCP Server

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Engineering memory for AI-assisted codebases: decisions, bug lineage and invariants, over MCP.

About

Engineering memory for AI-assisted codebases: decisions, bug lineage and invariants, over MCP.

Security Report

7.2
Moderate7.2Low Risk

Hunch is a well-architected engineering memory system for codebases with strong design principles around security and determinism. The codebase demonstrates careful attention to credential handling, subprocess safety, and permission scoping. However, several moderate-risk findings exist: subprocess invocations lack comprehensive input validation in some paths, environment variable handling could be more restrictive in synthesis flows, and there are areas where error handling could be more defensive. The permissions requested align well with the tool's purpose (filesystem access for memory graphs, network for optional LLM synthesis, git operations), and there are no signs of malicious intent or data exfiltration. Package verification found 1 issue.

4 files analyzed · 8 issues found

Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.

Permissions Required

This plugin requests these system permissions. Most are normal for its category.

File System Read

Reads files on your machine. Normal for tools that analyze or process local data.

File System Write

Writes or modifies files on your machine. Check that this is expected for the tool.

HTTP Network Access

Connects to external APIs or services over the internet.

env_vars

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Shell Command Execution

Runs commands on your machine. Be cautious — only use if you trust this plugin.

process_spawn

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system_info

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How to Install

Add this to your MCP configuration file:

{
  "mcpServers": {
    "io-github-davesheffer-hunch": {
      "args": [
        "-y",
        "@davesheffer/hunch"
      ],
      "command": "npx"
    }
  }
}

Documentation

View on GitHub

From the project's GitHub README.

Hunch

Give your AI coding assistant the missing story behind your code.

npm version GitHub stars license

Git remembers what changed. Chat history disappears. A future Claude, Cursor, Codex, or Copilot session can read your code, but it usually does not know why your team chose this design, which alternative failed, or which old bug a strange-looking line prevents.

Hunch is project memory for the AI coding tools you already use. It saves decisions, bug fixes, rejected approaches, and important rules. Before an assistant changes code, Hunch brings back the relevant reasons. After the change, it can check whether the work conflicts with a rule your team explicitly trusts.

A simple example

Your team once moved login sessions to the server so stolen tokens could be disabled immediately. Months later, an AI assistant sees the extra code and proposes a “simpler” token-only design. Hunch shows the assistant why the server-side design exists and which security bug it prevents—before the edit happens.

That means less time repeating old explanations, fewer old mistakes returning, and the same project context across every coding assistant.

Hunch is not another AI model and it does not replace your coding assistant. It is the memory and safety layer behind it. Memory is advisory by default; nothing blocks work unless you deliberately turn on strict checks for a precise rule.

Start in five minutes

Requires Node 22.13+ and a git repository.

npm i -g @davesheffer/hunch
cd your-repo
hunch init
hunch backfill --since 90d   # optional: seed memory from recent history

Reload your coding assistant, then ask a normal question:

Why is this built this way?

Hunch answers from your project's saved history and shows where the answer came from. hunch init indexes the repo, installs local hooks, and connects supported assistants without replacing their existing configuration.

What Hunch gives you

  • A memory that outlives chat — decisions and corrections are still available next week, next year, and in a different assistant.
  • One shared story — Claude Code, Cursor, Copilot, Windsurf, Antigravity, Codex, and any MCP client get the same project context.
  • Warnings with reasons — review a change against trusted project rules and see exactly why it passes, needs attention, or should be blocked.
  • Past bugs stay useful — see which old incident a piece of code fixed before accidentally undoing it.
  • Understands how code connects — for TypeScript, JavaScript, Python, Go, PHP, YAML, and Helm, Hunch can see what calls or depends on the code you are about to change. Its memory works with any language.
  • Works with existing decision documents — import your architecture decision records into Hunch, or export Hunch decisions back to a standard format other tools can read. Imported ADRs start as useful advisory memory; during normal work your assistant asks you to approve or decline one exact ADR at a time. Silence never grants authority, and changed ADR text is asked again.

The source of truth is readable JSON in .hunch/. A local SQLite index makes retrieval fast but is always rebuildable.

What improved in v1.19

Hunch now gives developers a better, shorter list of code to inspect when they describe a problem. In a 12-problem test on unfamiliar code, it found the changed piece of code in 6 cases instead of 3 and found the correct file in 10 cases instead of 8. In a separate test, it kept the same five successful finds while reducing the average number of named code items to inspect—such as functions or classes—from 18.9 to 11.

What the test measuredBeforev1.19Result
Problems where Hunch found the changed code3/126/122× as many in this test
Problems where Hunch found the correct file8/1210/122 more correct files
Pieces of code inspected for the same five finds18.9 average11 average41.9% less to inspect

These are small, controlled tests—not a promise that Hunch is twice as accurate everywhere. Hunch also refuses to pretend it knows the exact fix when the evidence only shows where to investigate. The detailed receipts live in bench/external/results.

See the public roadmap for what is next and what is deliberately out of scope.

Common tasks

Most memory work happens automatically after commits. These commands cover the common manual paths:

CommandUse it for
hunch why <file>Explain why a file is built this way and what could be affected by changing it
hunch query "<question>"Search project memory
hunch context "<task>" --profile reviewerGet a bounded builder, reviewer, or architect view without changing enforcement
hunch change-id <base> [head]Bind a branch and its exact squash merge to the same content-based change ID
hunch check --workingCheck current changes against the decisions and rules your team trusts
hunch logSee what Hunch remembered and undo a memory change if needed
hunch escalationsSee the rare questions that need a human answer
hunch reviewAnswer the current imported-ADR approve/decline question from the terminal
hunch doctorDiagnose setup problems

These tools help researchers and maintainers investigate where a described behavior may live. They show uncertainty instead of claiming to know the exact fix.

CommandUse it for
hunch shortlist --issue "..."Build a bounded list of files and named code items to inspect
hunch evidence-map receipt.jsonAdd observed execution evidence without guessing the exact owner

hunch evidence-map accepts a bounded JSON receipt containing a red target, a distinct green control, optional execution counts, and optional intervention outcomes. It reports target-only and shared execution plus behavior-sensitive files. It does not run the probes, edit the repository, or claim that behaviorally influential code owns the correction. Use --json for the machine-readable map; MCP clients can submit the same receipt through hunch_evidence_map.

hunch shortlist --evidence attaches authenticated observations to the relevant candidates but does not reorder them. Three fresh transfer experiments failed to prove that execution or intervention influence identifies the correction owner, so the production path converts that result into a hard safeguard: no candidate is promoted or displaced by evidence. JSON output still includes a deterministic receipt and the explicit exact_owner_enabled: false policy.

Every shortlist also preserves its flat top five and adds a deterministic hierarchical inspection view anchored to those files: at most five files, two semantic declaration families per file, and three declarations per family. On a preregistered 12-case fresh transfer, the preserved union found 6/12 changed declarations versus 3/12 for the flat top five (+25 percentage points, three rescues), while correct-file coverage improved from 8/12 to 10/12. The view averaged 18.8 unique declarations and never exceeded 24. This promotes the clusters as a supplemental diagnostic, not as a top-five accuracy claim; exact-owner output and per-case confidence remain disabled. JSON output includes the deterministic cluster receipt and the transfer calibration.

The default output also turns those clusters into a progressive inspection queue. It preserves the flat shortlist, adds only the strongest members of already-selected semantic families, stops at ten when the behavior is explained, and permits one final fallback declaration before reporting uncertainty. Development replay retained all 21/36 combined hits from the full cluster view while reducing the hard inspection ceiling to 11 from an average of 19.8 declarations (44% less). On a separate preregistered 12-case ArkType transfer it retained all 5 full-cluster hits with zero losses and reduced mean inspection from 18.9 declarations to 11 (41.9% less). It found no additional fresh hit, so the queue is retained as an efficiency advisory rather than promoted as an accuracy gain.

Follow-up optimization attempts stay out of production. Replacing cluster slots with same-file declarations produced four development rescues but also three losses. Appending two same-file slots removed those development losses, but a second blind 12-case ArkType transfer produced 3/12 hits for both the existing and expanded plans, with zero rescues. Product-source filtering lost one prior hit, one-hop relationship expansion added none, and evidence/causal rerankers also failed their frozen transfer gates. The receipts remain in bench/external/results; rejected mechanisms cannot silently change the production ordering.

Corrections can become scoped rules, but captured memory cannot hard-block on its own. Enforcement is deterministic and opt-in:

hunch firmness strict
hunch check --staged --strict

Share the same memory with your team

For a team, Hunch can keep everyone’s decisions, corrections, and rules in one private Git repository, separate from the code repository. Hunch does not host it. Create a private repository that every teammate can access, install Hunch on team machines and CI, then have one maintainer run:

npm i -g @davesheffer/hunch@1.20.2
hunch shared --repo git@github.com:acme/project-hunch-memory.git
git add .gitignore .hunch/team.json
git commit -m "chore: connect shared Hunch memory"
git push

Use a credential-free URL in the command; keep tokens in your Git credential helper or use SSH. If this project already publishes memory in .hunch/ and you want to move it into the dedicated repo, add --migrate, review the reported untrack/ignore changes, and follow the commit instructions printed by Hunch. Omit --migrate for a new setup.

After the pointer commit lands, teammates need Hunch installed and Git access to the memory repo:

npm i -g @davesheffer/hunch@1.20.2
git pull
hunch init
hunch doctor

hunch init validates and connects an ignored local clone of the memory repo. Memory-reading and writing CLI operations attempt a bounded refresh at startup; connected MCP sessions check for new team memory at each tool-request boundary and rebuild their local index only when the JSON changed. New captures route to that repo and are committed and synchronized automatically by default. If a push cannot complete, a later capture or hunch shared --sync retries it.

The committed .hunch/team.json contains only the credential-free memory-repo locator and canonical branch. The ignored .hunch/local.json contains local paths and preferences, not credentials; authentication stays in SSH or the normal Git credential helper. Shared memory records, .hunch/local.json, and .hunch-private/ stay out of code history. Use hunch check --base origin/main --strict --public-only --format markdown for output that may be posted publicly; omit --public-only for an internal check that should enforce team memory. HUNCH_PRIVATE_DIR remains an explicit process-level override for CI and portability. When it redirects a repo away from .hunch/local.json or bypasses an advertised team store, CLI and MCP startup warn on stderr and hunch doctor labels the effective source.

For a correction that Hunch can express as a deterministic policy, create and inspect its proof-backed proposal:

hunch policy upgrade-correction con_...
hunch policy card pol_...

The upgrade creates evidence, a plan, and a proof but leaves the policy proposed with authority: none. A proved policy still requires explicit, audited human acceptance before it can become advisory or blocking; Hunch never grants that authority automatically.

Need to pause or roll back without deleting memory?

hunch firmness off
hunch shared --repo git@github.com:acme/project-hunch-memory.git --no-auto-commit
# Later, publish any pending local memory explicitly:
hunch shared --sync

The first command turns off agent-hook enforcement; the second keeps shared reads and local captures but stops automatic memory commits and pushes. As a team-coordinated rollback, revert the setup commit to stop discovery after teammates pull the revert. Existing machines retain their ignored local overlay until they are deliberately disconnected; do not delete the memory repo as part of a rollback. For this rollout, reinstall the previous published package with npm i -g @davesheffer/hunch@1.20.1; the release receipt resolves and records the verified rollback target from the npm registry instead of trusting Git tags. Pause enforcement first as shown above, and keep every team client on the same release before resuming Matrix policy workflows.

Synthesis without surprise billing

Hunch can draft structured memory through:

  • a selected Claude Code, Codex, or Cursor subscription CLI;
  • an opt-in OpenAI-compatible local endpoint such as Ollama, vLLM, LM Studio, or llama.cpp; or
  • the built-in deterministic fallback when no model is available.

When several subscription CLIs are installed, Hunch does not guess which plan to use:

hunch provider codex-cli

Local and private-network endpoints work without a billing flag. Every public remote requires the explicit HUNCH_SYNTH_ALLOW_METERED=1 opt-in, because Hunch cannot infer cost from a hostname. See Synthesis & billing for setup details.

Local-first and portable

Hunch has no hosted memory service or telemetry. Your graph travels with git and speaks MCP, so it is not tied to one editor or model provider.

Sensitive reasoning can live in a separate private overlay:

hunch private --repo git@github.com:you/project-memory.git

Local tools see the combined graph; public CI and committed documentation stay public-only.

Releases you can trace to source

Hunch releases are built and tested without publication credentials. The resulting npm tarball or VSIX is content-addressed, carried unchanged into a minimal publisher, and checked again against the registry after publication. The npm path also runs native, atomic-write, and Matrix safety checks on Windows and macOS and verifies provenance back to the exact source tag.

The editor companion is published from an exact vscode-v* tag to Open VSX. The workflow verifies the downloaded public VSIX has the same digest as the credential-free release candidate.

Learn more

Apache-2.0

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