@agentistics/mcp

Name: @agentistics/mcp Review
Item: @agentistics/mcp
Rating: 2.8
Author: Aaron Matthews

Connector Data & Analytics Usable

Works inClaude Code Claude Cowork Claude Chat

Usable Scanned — metadata only

Enables real-time code analytics and performance insights directly within Claude workflows, reducing feedback loops between analysis and development without …

Agentistics MCP server — Claude Code analytics for Claude Desktop and Claude Code

Ask Claude to analyze code metrics across your repository and identify performance bottlenecks
Generate a summary of test coverage gaps in your codebase to prioritize testing efforts
Find unused functions and dependencies cluttering your project to plan refactoring work

46 starsFSL-1.1-ALv2FreeNo code needed

Usable rating — This tool is functional but has notable gaps. Review the evaluation notes below before deploying.

Why it matters

Enables real-time code analytics and performance insights directly within Claude workflows, reducing feedback loops between analysis and development without context switching or manual data exports.

Best for

Engineering teams using Claude Code for continuous integration monitoring and code quality assessment across CI/CD pipelines.

Works in

Claude Code Claude Cowork Claude Chat

Source

https://www.npmjs.com/package/@agentistics/mcp

By GitHub Actions

How to Get It

Option 1: Claude Desktop AppOpen the Customize panel in the sidebar → browse connectors → search and add. Works in Claude Code, Claude Cowork, and Claude Chat.

Option 2: Paste into Claude CodeCopy the command below and paste it into a Claude Code conversation. Claude will run it for you.

Command

npx -y @agentistics/mcp

Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.

Auto-generated from the tool's public listing — not hands-on verified. Cross-check against the source repo's README before running.

First thing to try

Once it’s connected, paste this into Claude:

Analyze code metrics across my repository and identify performance bottlenecks

CostFree

Trust Signals Auto-scanned

Stars46Contributors10Last updated2026-10-27LicenseFSL-1.1-ALv2Weekly downloads12Known CVEsNone foundSources: GitHub Advisory Database + OSV.dev · Scanned 2026-10-27 · scanner v1

Data & Access

Data processingPrompts sent to Anthropic API. Enterprise/Team plans exclude training.

Reviewer notes

Auto-scanned review. These are observations, not a security certification.

Scored from trust signals (evidence-eval-v1): 44 GitHub stars; contributors unknown; last commit 0d ago; license MIT.

Things to check

Scanned, not hands-on tested — this entry was auto-scanned from public metadata (GitHub metrics, license, security flags). No reviewer has run it, and no tool-specific limitations have been documented yet.

How to evaluate tools before deploying →

Data shown here comes from public APIs and automated scanning. Reviewer notes reflect one person's experience. This is not a security certification or legal recommendation. Always evaluate tools according to your own organization's policies.

Evaluation Scores

Evaluation

Ease of Use

3/5

Versatility

2/5

Reliability

3/5

Security

3/5

Overall score2.75 / 5.00 UsableEvaluatedSep 2026

Scored from trust signals (evidence-eval-v1): 44 GitHub stars; contributors unknown; last commit 0d ago; license MIT.

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