Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Model Context Protocol (MCP) client - connect to tools, data sources and services
Model Context Protocol (MCP) client - connect to tools, data sources and services
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Implementation of the Model Context Protocol (MCP) client for connecting to tools and data sources.
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
# Install Python dependencies (requests is the only required dependency) pip install requests
.\mcp.ps1 -Action connect -ServerUrl "https://mcp-server.com" -ApiKey "your-key"
.\mcp.ps1 -Action tools -ServerUrl "https://mcp-server.com"
.\mcp.ps1 -Action call -ServerUrl "https://mcp-server.com" -ToolName "search" -Arguments '{"query": "AI agents"}'
.\mcp.ps1 -Action resources -ServerUrl "https://mcp-server.com"
.\mcp.ps1 -Action read -ServerUrl "https://mcp-server.com" -ResourceUri "file:///data/config.json"
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
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
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)
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.
Only use MCP servers you control or trust Don't connect to random public MCP servers Review what tools/resources are available before using
Review what tools/resources are available before using Python 3.8+ requests library
MIT
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