| name | discourse-mcp-connector |
| description | MCP connector for Discourse forum platform – enables AI-powered forum management, topic curation, and community engagement through Claude |
| license | GPL |
| tags | ["dev","communication","mcp","discourse","forum"] |
| difficulty | intermediate |
| time_to_master | 4-8 weeks |
| version | 1.0.0 |
Discourse MCP Connector
Overview
This skill enables Claude to interact with Discourse through the Model Context Protocol (MCP). It provides a bridge between Claude's AI capabilities and Discourse's REST API, allowing natural language control of Discourse operations, intelligent automation, and AI-powered assistance for Discourse workflows.
When to Use This Skill
- Topic creation and category management
- Post summarization and thread analysis
- User trust level management
- Plugin and theme configuration
- Community analytics and reporting
Architecture
┌─────────────┐ ┌─────────────────┐ ┌──────────────────┐
│ Claude │────▶│ MCP Server │────▶│ Discourse │
│ (Client) │◀────│ (TypeScript) │◀────│ (REST API )│
└─────────────┘ └─────────────────┘ └──────────────────┘
Core Concepts
MCP Server Setup
The connector implements an MCP server that exposes Discourse operations as tools Claude can invoke. The server translates natural language intentions into REST API calls.
Key Endpoints/Interfaces
/topics.json, /posts.json, /categories.json, /admin/users.json, /search.json
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: "discourse-mcp-connector",
version: "1.0.0",
});
server.tool(
"list_resources",
"List and query Discourse 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 }) => {
const response = await fetch(`${BASE_URL}/topics.json`, {
headers: { "Authorization": `Bearer ${API_KEY}` },
});
const data = await response.json();
return {
: [{ : , : .(data, , ) }],
};
}
);
server.(
,
,
{
: z.().(),
: z.({}).().().(),
},
({ name, config }) => {
response = (, {
: ,
: {
: ,
: ,
},
: .({ name, ...config }),
});
data = response.();
{
: [{ : , : }],
};
}
);
server.(
,
,
{
: z.().(),
: z.().().(),
},
({ , timeframe }) => {
response = (, {
: { : },
});
data = response.();
{
: [{ : , : .(data, , ) }],
};
}
);
transport = ();
server.(transport);
Claude Desktop Configuration
{
"mcpServers": {
"discourse-mcp-connector": {
"command": "node",
"args": ["path/to/discourse-mcp-connector/index.js"],
"env": {
"DISCOURSE_API_KEY": "your-api-key",
"DISCOURSE_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 Discourse 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 Discourse API; sanitize outputs
- Logging: Log all API interactions for debugging and audit purposes
Example Prompts
"Create a new category for Feature Requests and pin an introductory topic with submission guidelines"
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
Changelog
| Version | Date | Changes |
|---|
| 1.0.0 | 2026-04-01 | Initial MCP connector skill |
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