MCP Support

Complete guide to Model Context Protocol (MCP) integration with ToolUniverse

ToolUniverse provides comprehensive support for the Model Context Protocol (MCP), enabling seamless integration with AI scientists, reasoning models, and agentic systems. This guide covers everything you need to know about using ToolUniverse through MCP.

What is MCP?

The Model Context Protocol (MCP) is a standardized protocol that enables AI scientists to securely connect to external tools and data sources. ToolUniverse implements MCP through the Scientific Model Context Protocol (SMCP), extending standard MCP capabilities with scientific domain expertise.

Key Benefits: - Standardized Integration: Connect to any MCP-compatible AI scientist - Scientific Tool Access: Direct access to 649+ scientific tools - Intelligent Discovery: AI-powered tool search and recommendation - Secure Communication: Standardized protocol ensures secure tool execution - Production Ready: High-performance architecture for real-world applications

MCP Architecture Overview

AI Scientist (Claude, ChatGPT, Gemini, etc.)
        │ MCP Protocol
┌─────────────────┐
│ ToolUniverse    │ ← MCP Server
│   MCP Server    │
└─────────────────┘
        │ Tool Execution
┌─────────────────┐
│ Scientific      │
│ Tools (649+)    │
└─────────────────┘

ToolUniverse MCP Implementation

ToolUniverse provides three main MCP server implementations:

  1. `tooluniverse-smcp` - Full-featured server with configurable transport (HTTP, SSE, stdio)

  2. `tooluniverse-smcp-stdio` - Specialized server for stdio transport (optimized for desktop AI applications)

All servers expose the same comprehensive set of 649+ scientific tools through the MCP protocol.

Quick Start

For basic MCP server setup and configuration, see the comprehensive guide in MCP Server Functions.

CLI Options Reference

The following are commonly used command-line flags for ToolUniverse MCP servers.

tooluniverse-smcp [OPTIONS]

--port INT                     Server port (HTTP/SSE). Default: 7000
--host TEXT                    Bind host for HTTP/SSE. Default: 0.0.0.0
--transport [http|stdio|sse]   Transport protocol. Default: http
--name TEXT                    Server display name
--max-workers INT              Worker pool size for tool execution
--verbose                      Enable verbose logs

# Tool selection
--categories STR...            Include only these categories
--exclude-categories STR...    Exclude these categories
--include-tools STR...         Include only these tool names
--tools-file PATH              File with one tool name per line
--include-tool-types STR...    Include only these tool types
--exclude-tool-types STR...    Exclude these tool types
--tool-config-files TEXT       Mapping like "custom:/path/to/custom.json"

# Hooks
--hooks-enabled                Enable hooks (default: False)
--hook-type [SummarizationHook|FileSaveHook]
--hook-config-file PATH        JSON config for hooks
tooluniverse-smcp-stdio [OPTIONS]

--name TEXT                    Server display name
--categories STR...            Include only these categories
--include-tools STR...         Include only these tool names
--tools-file PATH              File with one tool name per line
--include-tool-types STR...    Include only these tool types
--exclude-tool-types STR...    Exclude these tool types
--hooks                        Enable hooks (default: disabled for stdio)
--hook-type [SummarizationHook|FileSaveHook]
--hook-config-file PATH        JSON config for hooks

Configuration

All MCP servers support configuration through command-line arguments. See the CLI Options Reference above for available configuration options.

Configuration Files

Example tools file (one tool per line, lines starting with # are comments):

# tools.txt
OpenTargets_get_associated_targets_by_disease_efoId
Tool_Finder_LLM
ChEMBL_search_similar_molecules
# Tool_Finder_Keyword

Example hook config file:

{
  "SummarizationHook": {
    "max_tokens": 2048,
    "summary_style": "concise"
  },
  "FileSaveHook": {
    "output_dir": "/tmp/tu_outputs",
    "filename_template": "{tool}_{timestamp}.json"
  }
}

Client Integration Examples

Python MCP client (conceptual) connecting to HTTP server:

import requests

# Discover tools
tools = requests.get("http://127.0.0.1:8000/mcp/tools").json()

# Execute a tool
payload = {
    "name": "UniProt_get_entry_by_accession",
    "arguments": {"accession": "P04637"}
}
result = requests.post("http://127.0.0.1:8000/mcp/run", json=payload).json()
print(result)

JavaScript MCP client (conceptual) against HTTP server:

  const fetch = require('node-fetch');

  async function run() {
    const toolsResp = await fetch('http://127.0.0.1:8000/mcp/tools');
    const tools = await toolsResp.json();
    console.log('Tools:', tools.length);

    const resp = await fetch('http://127.0.0.1:8000/mcp/run', {
      method: 'POST',
      headers: { 'Content-Type': 'application/json' },
      body: JSON.stringify({
        name: 'UniProt_get_entry_by_accession',
        arguments: { accession: 'P04637' }
      })
    });
  const result = await resp.json();
  console.log(result);
}
 run();

Streaming Output

All MCP-exposed tools now accept an optional _tooluniverse_stream flag. When set to true, compatible tools send incremental text chunks as MCP log notifications while still returning the final result payload at completion. Example request payload:

{
  "method": "tools/call",
  "params": {
    "name": "AgenticTool_example",
    "arguments": {
      "question": "Summarise recent literature",
      "_tooluniverse_stream": true
    }
  }
}

Make sure your client surfaces notifications/log (FastMCP ctx.info) messages to display the streamed output.

Claude Desktop stdio registration (example):

{
  "mcpServers": {
    "tooluniverse": {
      "command": "tooluniverse-smcp-stdio",
      "args": ["--categories", "uniprot", "ChEMBL", "opentarget", "--hooks", "--hook-type", "SummarizationHook"]
    }
  }
}

MCP Server Configuration

Transport Options

ToolUniverse MCP servers support multiple transport protocols:

HTTP Transport (Default)
  • Best for web-based applications and remote access

  • Supports RESTful API endpoints

  • Configurable host and port

STDIO Transport
  • Optimized for desktop AI applications

  • Direct process communication

  • Lower latency for local applications

Server-Sent Events (SSE)
  • Real-time streaming capabilities

  • Suitable for interactive applications

  • Supports long-running operations

Tool Selection

Configure which tools are available through the MCP server. For detailed configuration options including category-based loading, tool-specific loading, and type-based filtering, see Category-Based Loading, Tool-Specific Loading, and Type-Based Filtering.

Advanced Configuration

Hook Configuration

Enable intelligent output processing hooks for MCP servers. For comprehensive hook configuration including SummarizationHook and FileSaveHook, see Hook Configuration.

See also

Detailed Guide: Server and Stdio Hook Integration - Complete hook integration tutorial

Performance Tuning

Optimize server performance for your use case. For detailed performance configuration options, see Server Configuration.

AI Scientist Integration

ToolUniverse MCP servers are compatible with major AI scientists and platforms:

Claude Desktop

Integrate ToolUniverse with Claude Desktop for powerful desktop-based scientific research.

See also

For complete Claude Desktop integration, see Claude Desktop

Tutorial: ToolUniverse MCP Integration with Claude Desktop App - Step-by-step Claude Desktop setup

ChatGPT API

Connect ToolUniverse to ChatGPT API for programmatic AI-scientist workflows.

See also

For ChatGPT API integration, see ChatGPT API

Gemini CLI

Use ToolUniverse with Gemini CLI for command-line scientific research.

See also

For Gemini CLI integration, see Gemini CLI

Tutorial: ToolUniverse MCP Integration with Gemini CLI - Complete Gemini CLI setup guide

Claude Code

Integrate ToolUniverse with Claude Code for IDE-based scientific development.

See also

For Claude Code integration, see Claude Code

Qwen Code

Connect ToolUniverse to Qwen Code for terminal-based scientific workflows.

See also

For Qwen Code integration, see Qwen Code

GPT Codex CLI

Use ToolUniverse with GPT Codex CLI for advanced command-line research capabilities.

See also

For GPT Codex CLI integration, see GPT Codex CLI

MCP Protocol Details

Tool Discovery

MCP clients can discover available tools through the standard MCP protocol. For detailed tool discovery methods and examples, see mcp-server-integration.

Tool Execution

Execute tools through the MCP protocol. For comprehensive tool execution patterns and MCP client examples, see mcp-client-integration.

Error Handling

MCP provides standardized error handling. For detailed error handling patterns and troubleshooting, see error-handling-validation.

MCP Server Management

Server Status

Monitor MCP server status and health. For server management commands and status monitoring, see Discovery Commands.

Logging and Debugging

Enable comprehensive logging for debugging. For detailed logging configuration and debugging options, see Method 2: Global Configuration.

Performance Monitoring

Monitor MCP server performance. For performance monitoring and optimization, see performance-optimization.

Troubleshooting

Common Issues

MCP Server Not Starting
  • Check if port is available

  • Verify ToolUniverse installation

  • Check server logs for error messages

Tools Not Available
  • Verify tool categories are loaded

  • Check tool names are correct

  • Ensure tools are not excluded

Connection Issues
  • Verify transport protocol matches client expectations

  • Check firewall settings for HTTP transport

  • Ensure proper authentication for remote connections

Performance Issues
  • Increase worker threads

  • Enable caching for repeated tool calls

  • Use specific tool categories instead of loading all tools

For comprehensive troubleshooting guide, see troubleshooting.

Debug Commands

Useful debugging commands and validation methods. For complete debugging command reference, see Discovery Commands.

Best Practices

Security

  • Use HTTPS in production environments

  • Implement proper authentication and authorization

  • Regularly update ToolUniverse and MCP dependencies

  • Monitor server logs for suspicious activity

Performance

  • Load only necessary tool categories

  • Use appropriate worker thread counts

  • Enable caching for frequently used tools

  • Monitor server metrics and adjust configuration

Reliability

  • Implement proper error handling in MCP clients

  • Use retry mechanisms for transient failures

  • Monitor server health and restart if needed

  • Keep backup configurations for critical deployments

For detailed best practices and production deployment guidance, see performance-optimization.

Summary

ToolUniverse’s MCP support provides a powerful, standardized way to integrate scientific tools with AI scientists. The SMCP implementation extends standard MCP capabilities with scientific domain expertise, making it easy to build sophisticated AI-scientist workflows.

Key takeaways:

  • Easy Integration: Simple setup with major AI scientists

  • Comprehensive Tools: Access to 649+ scientific tools through MCP

  • Flexible Configuration: Multiple transport options and tool selection

  • Production Ready: High-performance, secure, and reliable

  • Extensive Documentation: Complete guides for all major AI platforms

Start with the Building AI Scientists guide to begin building your AI scientist, or explore specific integrations for your preferred AI scientist.