iron-manus-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| ALLOWED_HOSTS | No | SSRF whitelist of allowed hosts, comma-separated (e.g., api.github.com,httpbin.org) | |
| KNOWLEDGE_TIMEOUT_MS | No | Request timeout in milliseconds for knowledge requests | |
| ENABLE_SSRF_PROTECTION | No | Enable SSRF protection (true/false) | |
| KNOWLEDGE_MAX_CONCURRENCY | No | API concurrency limit for knowledge requests |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| JARVISB | JARVIS Finite State Machine Controller - Implements the 8-phase agent loop (INIT → QUERY → ENHANCE → KNOWLEDGE → PLAN → EXECUTE → VERIFY → DONE) with Meta Thread-of-Thought orchestration. Features: Role-based cognitive enhancement through systematic thinking methodologies, meta-prompt generation for Task() agent spawning, fractal task decomposition, performance tracking, and single-tool-per-iteration enforcement. Enables Claude to autonomously manage complex projects through context segmentation. |
| APITaskAgentC | Specialized API research agent that orchestrates discovery, validation, and data fetching workflows. When you need structured data from external sources, ask: What type of evidence does my current research objective require? How can I ensure data reliability while maintaining research efficiency? This agent guides you through strategic API selection based on your cognitive role, automatically validates sources, and provides comprehensive data synthesis with actionable insights. |
| PythonComputationalToolC | Unified Python execution and data science tool with automatic library management and comprehensive workflow support |
| IronManusStateGraphC | Project-scoped FSM state management using knowledge graphs. Manage sessions, phases, tasks, and transitions with isolated state per project. |
| HealthCheckC | System intelligence assessment - evaluates not just operational health, but the cognitive readiness of your tools and infrastructure. When questioning system performance, ask: Are your tools thinking clearly? What might cognitive degradation look like in an AI system? This tool prompts you to consider: How do I assess whether my system is ready for intelligent decision-making, not just basic functionality? What early warning signs might indicate declining analytical capability? |
| SlideGeneratorB | Generates HTML slides from templates and content data. Takes template ID and structured content, returns rendered slide HTML. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 6 tools
JARVIS and IronManusStateGraph both deal with state management, creating potential confusion. Other tools like APITaskAgent, PythonComputationalTool, HealthCheck, and SlideGenerator are more distinct, but HealthCheck's abstract description adds ambiguity.
Most tools follow PascalCase (APITaskAgent, PythonComputationalTool, etc.), but JARVIS is an all-caps acronym outlier. There is no verb_noun pattern; names are descriptive nouns or proper names.
Six tools is a reasonable count for a multi-purpose server covering orchestration, API research, computation, state management, health check, and slide generation—neither too few nor too many.
The tool set mixes concrete (SlideGenerator) and abstract (HealthCheck) tools without clear domain coverage. Gaps exist in typical project management functions like file handling or user interaction, and some tools have vague purposes.