Geany MCP Connector
Overview
This skill enables Claude to interact with Geany through the Model Context Protocol (MCP). It provides a bridge between Claude's AI capabilities and Geany's Plugin API/CLI, allowing natural language control of Geany operations, intelligent automation, and AI-powered assistance for Geany workflows.
When to Use This Skill
- Build command generation and execution
- Project file management and navigation
- Tag-based code navigation with AI context
- Custom build target configuration
- Plugin and keybinding management
Architecture
┌─────────────┐ ┌─────────────────┐ ┌──────────────────┐
│ Claude │────▶│ MCP Server │────▶│ Geany │
│ (Client) │◀────│ (C/TypeScript) │◀────│ (Plugin API/CLI)│
└─────────────┘ └─────────────────┘ └──────────────────┘
Core Concepts
MCP Server Setup
The connector implements an MCP server that exposes Geany operations as tools Claude can invoke. The server translates natural language intentions into Plugin API/CLI calls.
Key Endpoints/Interfaces
document_open, build_execute, project_open, navqueue_goto, keybindings_set
Implementation
// Geany MCP Server Implementation
import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";
import { z } from "zod";
const server = new McpServer({
name: "geany-mcp-connector",
version: "1.0.0",
});
// Tool: List/Query Resources
server.tool(
"list_resources",
"List and query Geany resources with optional filters",
{
query: z.string().optional().describe("Search query or filter"),
limit: z.number().optional().describe("Max results to return"),
},
async ({ query, limit }) => {
// Call Geany Plugin API/CLI
const response = await fetch(`${BASE_URL}document_open`, {
headers: { "Authorization": `Bearer ${API_KEY}` },
});
const data = await response.json();
return {
content: [{ type: "text", text: JSON.stringify(data, null, 2) }],
};
}
);
// Tool: Create Resource
server.tool(
"create_resource",
"Create a new resource in Geany",
{
name: z.string().describe("Resource name"),
config: z.object({}).passthrough().optional().describe("Resource configuration"),
},
async ({ name, config }) => {
const response = await fetch(`${BASE_URL}document_open`, {
method: "POST",
headers: {
"Authorization": `Bearer ${API_KEY}`,
"Content-Type": "application/json",
},
body: JSON.stringify({ name, ...config }),
});
const data = await response.json();
return {
content: [{ type: "text", text: `Created: ${JSON.stringify(data)}` }],
};
}
);
// Tool: Analyze/Report
server.tool(
"analyze",
"AI-powered analysis of Geany data",
{
type: z.string().describe("Analysis type"),
timeframe: z.string().optional().describe("Time range for analysis"),
},
async ({ type, timeframe }) => {
// Fetch data and provide AI analysis
const response = await fetch(`${BASE_URL}document_open`, {
headers: { "Authorization": `Bearer ${API_KEY}` },
});
const data = await response.json();
return {
content: [{ type: "text", text: JSON.stringify(data, null, 2) }],
};
}
);
// Start server
const transport = new StdioServerTransport();
await server.connect(transport);
Claude Desktop Configuration
{
"mcpServers": {
"geany-mcp-connector": {
"command": "node",
"args": ["path/to/geany-mcp-connector/index.js"],
"env": {
"GEANY_API_KEY": "your-api-key",
"GEANY_BASE_URL": "https://your-instance-url"
}
}
}
}
Best Practices
- Authentication: Store API keys securely using environment variables; never hardcode credentials
- Rate Limiting: Implement request throttling to respect Geany API rate limits
- Error Handling: Provide clear, actionable error messages for common failure scenarios
- Pagination: Handle paginated responses for large datasets efficiently
- Caching: Cache frequently accessed read-only data to reduce API calls
- Security: Validate all inputs before passing to the Geany API; sanitize outputs
- Logging: Log all API interactions for debugging and audit purposes
Example Prompts
"Set up a new C project with Makefile and compile the main target"
Security Considerations
- All API credentials must be stored as environment variables
- Implement input validation and sanitization for all tool parameters
- Use HTTPS for all API communications
- Follow the principle of least privilege for API token permissions
- Audit log all write operations for compliance tracking
Resources
- Geany Official Documentation
- MCP SDK Documentation: https://modelcontextprotocol.io
- MCP Server Examples: https://github.com/modelcontextprotocol/servers
- SkillGalaxy Repository: https://github.com/Sandeeprdy1729/skill_galaxy
Changelog
| Version | Date | Changes |
|---|---|---|
| 1.0.0 | 2026-04-01 | Initial MCP connector skill |
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