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ctx MCP Server

stevesolun/ctx

Score: 69.5 Rank #4151 MCP Server
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CTX Fit finds the cheapest AI coding setup that reliably works on your repository, then applies the winner as a reviewable change.

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Overview

stevesolun/ctx is a Python MCP server licensed under MIT. CTX Fit finds the cheapest AI coding setup that reliably works on your repository, then applies the winner as a reviewable change. Topics: agents, ai-agents, anthropic, automation, claude, claude-code, context-management, developer-tools, knowledge-graph, llm, micro-skills, obsidian, skills, wiki, real-time, recommendation-engine, skill-management, harness, llm-wiki, mcp.

Ranked #4151 out of 24846 indexed tools.

Ecosystem

Python MIT
agentsai-agentsanthropicautomationclaudeclaude-codecontext-managementdeveloper-toolsknowledge-graphllmmicro-skillsobsidianskillswikireal-timerecommendation-engineskill-managementharnessllm-wikimcp

Score Breakdown

StarsFreshnessIssue HealthContributorsDependents
Stars 15% 588

588 stars → growing community

Freshness 25% 29d ago

Last commit 29d ago → recently updated

Issue Health 25% 27%

3/11 issues closed → many open issues

Contributors 10% 5

5 contributors → small team

Dependents 25% 0

No dependents → no downstream usage

npm Downloads N/A
PyPI Downloads N/A
Forks 69
Description Good
License MIT

Weights: Freshness 20% · Issue Health 20% · Dependents 22% · Stars 10% · Contributors 8% · How we score →

How to Improve

Description low impact

Expand your description to 150+ characters for better discoverability

Issue Health high impact

You have 8 open vs 3 closed issues — triaging stale issues improves health

Dependents medium impact

No downstream dependents detected yet — adoption by other projects is the strongest trust signal

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Matched Queries

"mcp server""mcp-server"topic:mcp

From the README

# ctx

**Find the cheapest AI coding setup that actually works on your repo.**

CTX Fit analyzes your repository, tests promising AI coding configurations
against real tasks in it, and produces the winning configuration as a
reviewable change — in your working tree with `--apply`, or as a pull request
with `--pr`. It picks the *cheapest* setup that *reliably* works — reliability
is a requirement, not a tie-break — and if nothing beats what you already have,
it says so.

The winner is chosen by a fixed rule, not a score: discard every candidate
below the reliability floor, then minimize attributable cost, then break ties
toward the simpler configuration. An LLM may explain a result; it never
decides one.

> **Release scope (1.0.21).** CTX Fit compares capability configurations within
> one coding-agent harness; it does not compare Codex, Claude Code, or other
> harnesses against one another. It recognizes and can run repository-native
> verification commands for Python, JavaScript/TypeS
Read full README on GitHub →

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