knot.mcp

The knot.mcp library provides MCP (Model Context Protocol) functionality for scripts, including tool discovery and execution.

Functions

Usage

import knot.mcp as mcp

# List all available tools
tools = mcp.list_tools()
for tool in tools:
    print(f"Tool: {tool['name']} - {tool['description']}")

# Search for space-related tools
results = mcp.tool_search("list spaces")
print(results)

# Execute a tool
spaces = mcp.execute_tool("list_spaces", {})
print(spaces)

Function Details

list_tools()

Get a list of all available MCP tools, including tools from remote MCP servers if configured.

Returns: list - List of tool objects with name, description, and parameters (JSON Schema).

tool_search(query, max_results=10)

Search for tools by keyword.

Parameters:

• query (string): Search query
• max_results (int, optional): Maximum results to return (default: 10)

Returns: list - Matching tools

execute_tool(name, arguments)

Execute a discovered tool.

Parameters:

• name (string): Tool name
• arguments (dict): Arguments to pass to the tool

Returns: any - The tool’s response, automatically decoded from JSON if applicable.

call_tool(name, arguments)

Low-level tool execution. For most cases, use execute_tool() instead.

Parameters:

• name (string): Tool name
• arguments (dict): Arguments to pass

Returns: any - Tool response

MCP Tool Development

For creating MCP tools, use scriptling.mcp.tool for portable parameter access:

import scriptling.mcp.tool as tool
import knot.space

# Get parameters
name = tool.get_string("name")
count = tool.get_int("count", 1)

# Use knot libraries
space = knot.space.get(name)

# Return result
tool.return_object(space)

Remote Tools

Tools from remote MCP servers have a namespace prefix:

import knot.mcp as mcp

# Call a remote tool
response = mcp.call_tool("ai.generate-text", {
    "prompt": "Write a hello world function",
    "max_tokens": 50
})
print(response)