What is ironcontext?

altrusianco/ironcontext — explained in plain English

Analysis updated 2026-05-18

★ 1RustAudience · developerComplexity · 3/5LicenseSetup · easy

Mindmap

mindmap
  root((ironcontext))
    What it does
      Scans MCP manifests
      Detects prompt injection
      Reasoning Impact Score
      Trims tool descriptions
    Tech stack
      Rust core
      Python wrapper
      TypeScript wrapper
      GitHub Action
    Use cases
      CI security gate
      Manifest auditing
      Token cost reduction
    Audience
      AI agent builders
      MCP server authors

mindmap root((ironcontext)) What it does Scans MCP manifests Detects prompt injection Reasoning Impact Score Trims tool descriptions Tech stack Rust core Python wrapper TypeScript wrapper GitHub Action Use cases CI security gate Manifest auditing Token cost reduction Audience AI agent builders MCP server authors

What do people build with it?

USE CASE 1

Scan an MCP tool manifest for prompt injection and hidden instruction attacks before an AI agent uses it.

USE CASE 2

Add IronContext as a GitHub Action step to catch malicious tool descriptions in CI.

USE CASE 3

Score MCP tools for hallucination risk with the Reasoning Impact Score.

USE CASE 4

Prune verbose tool descriptions to reduce token usage and cost.

What is it built with?

RustPythonTypeScriptGitHub Actions

How does it compare?

	altrusianco/ironcontext	abc3dz/mixxx	abyo-software/ferro-stash
Stars	1	1	1
Language	Rust	Rust	Rust
Setup difficulty	easy	moderate	moderate
Complexity	3/5	2/5	4/5
Audience	developer	general	ops devops

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · easy Time to first run · 5min

Install via cargo, pip, or npm, the wrappers call the same Rust binary.

Permissive open-source license, use freely for any purpose including commercial use, as long as you keep the copyright notice.

So what is it?

IronContext is a security and optimization tool for AI agents that use the Model Context Protocol (MCP). MCP is a standard way for AI assistants to discover and use external tools. Each tool comes with a description written in natural language that gets loaded directly into the AI's working memory, its context window. This creates a security risk: a maliciously crafted tool description can act like a hidden instruction, tricking the AI into doing something harmful, a technique called prompt injection. IronContext scans those tool descriptions before or during use, checking them against a set of known attack patterns (the May 2026 CVE pattern pack, rules CC-001 through CC-010) to catch things like invisible Unicode characters, script mixing tricks that disguise malicious tool names, hidden instructions, and attempts to get the AI to echo secrets. It also assigns each tool a Reasoning Impact Score (RIS) from 0 to 100, estimating how likely a tool's description is to cause the AI to behave unexpectedly or hallucinate. Beyond security, IronContext trims verbose tool descriptions to reduce how many tokens they consume in the AI's context, which lowers cost and can improve reasoning quality. The tool is built in Rust for speed, with scans completing in under 10 milliseconds on a 100 tool manifest. It can be called from a command line, integrated through Python or TypeScript wrappers, or added as a one step GitHub Action for automated CI checks. Results can be output as plain text, JSON, or SARIF format for use with GitHub Code Scanning. The project is Apache 2.0 licensed.

Copy-paste prompts

Prompt 1

How do I run ironcontext scan on my MCP manifest.json and interpret the CC-001 through CC-010 findings?

Prompt 2

Set up an IronContext GitHub Action step that fails CI on high severity findings and uploads a SARIF report.

Prompt 3

Show me how to call ironcontext from Python to check if a manifest has security issues.

Prompt 4

Explain what a Reasoning Impact Score of 80 out of 100 means for one of my MCP tools.

Frequently asked questions