✓ Verified 💻 Development ✓ Enhanced Data

Mcp Client

Model Context Protocol (MCP) client - connect to tools, data sources and services.

Rating: 4.3 (453 reviews)
Downloads: 855 downloads
Version: 1.0.0

Overview

Model Context Protocol (MCP) client - connect to tools, data sources and services.

✨Key Features

Connect to MCP Servers - Access tools and resources from MCP-enabled services

Tool Invocation - Call tools exposed by MCP servers

Resource Access - Read files, databases, APIs

Prompt Templates - Use structured prompts from MCP servers

Complete Documentation

View Source →

MCP Client Skill

Implementation of the Model Context Protocol (MCP) client for connecting to tools and data sources.

What it does

Connect to MCP Servers - Access tools and resources from MCP-enabled services
Tool Invocation - Call tools exposed by MCP servers
Resource Access - Read files, databases, APIs
Prompt Templates - Use structured prompts from MCP servers

Installation

powershell

# Install Python dependencies (requests is the only required dependency)
pip install requests

Usage

Connect to MCP Server

powershell

.\mcp.ps1 -Action connect -ServerUrl "https://mcp-server.com" -ApiKey "your-key"

List Available Tools

powershell

.\mcp.ps1 -Action tools -ServerUrl "https://mcp-server.com"

Call a Tool

powershell

.\mcp.ps1 -Action call -ServerUrl "https://mcp-server.com" -ToolName "search" -Arguments '{"query": "AI agents"}'

List Resources

powershell

.\mcp.ps1 -Action resources -ServerUrl "https://mcp-server.com"

Read a Resource

powershell

.\mcp.ps1 -Action read -ServerUrl "https://mcp-server.com" -ResourceUri "file:///data/config.json"

MCP Concepts

MCP Server: Service that exposes tools, resources, and prompts
Tools: Functions the LLM/agent can call
Resources: Data sources (files, APIs, DBs)
Prompts: Pre-defined prompt templates

API Reference

text

POST /mcp/connect     - Connect to server
GET  /mcp/tools       - List available tools
POST /mcp/call       - Invoke a tool
GET  /mcp/resources  - List resources
GET  /mcp/read       - Read resource
GET  /mcp/prompts    - List prompt templates

Examples

Python Usage

python

from mcp_client import MCPClient

client = MCPClient("https://mcp-server.com", api_key="key")

# List tools
tools = client.list_tools()
print(tools)

# Call tool
result = client.call_tool("search", {"query": "quantum"})
print(result)

# Read resource
data = client.read_resource("file:///config.json")
print(data)

⚠️ Security Warnings

file:// URI Risk

The MCP protocol allows file:///path URIs to read files from the server. Only connect to trusted MCP servers. A malicious server could exfiltrate sensitive files.

Best Practices

Only use MCP servers you control or trust
Don't connect to random public MCP servers
Review what tools/resources are available before using

Requirements

Review what tools/resources are available before using
Python 3.8+
requests library

License

MIT

Installation

Terminal bash


openclaw install mcp-client

Copied!

💻Code Examples

pip install requests

pip-install-requests.txt

## Usage

### Connect to MCP Server

.\mcp.ps1 -Action read -ServerUrl "https://mcp-server.com" -ResourceUri "file:///data/config.json"

mcpps1--action-read--serverurl-httpsmcp-servercom--resourceuri-filedataconfigjson.txt

## MCP Concepts

- **MCP Server**: Service that exposes tools, resources, and prompts
- **Tools**: Functions the LLM/agent can call
- **Resources**: Data sources (files, APIs, DBs)
- **Prompts**: Pre-defined prompt templates

## API Reference

GET /mcp/prompts - List prompt templates

get-mcpprompts---list-prompt-templates.txt

## Examples

### Python Usage

example.txt

POST /mcp/connect     - Connect to server
GET  /mcp/tools       - List available tools
POST /mcp/call       - Invoke a tool
GET  /mcp/resources  - List resources
GET  /mcp/read       - Read resource
GET  /mcp/prompts    - List prompt templates

example.py

from mcp_client import MCPClient

client = MCPClient("https://mcp-server.com", api_key="key")

# List tools
tools = client.list_tools()
print(tools)

# Call tool
result = client.call_tool("search", {"query": "quantum"})
print(result)

# Read resource
data = client.read_resource("file:///config.json")
print(data)