Tencent RTC SDK MCP Server Guide

This repository provides a CLI-based Model Context Protocol (MCP) Server that exposes Tencent RTC SDK documentation and API resources to LLM tools, helping AI agents deliver more accurate implementation guidance and integration support.

Features

• Efficient retrieval: Supports Tencent RTC documentation retrieval for fast access to official references and best practices.
• Broad coverage: Covers Chat (IM), Call, Live, Room, RTCEngine (TRTC SDK), and TIMPush domains.
• Intelligent routing: Supports product/platform intent disambiguation and prompts for missing platform/framework information when needed.
• Integration-friendly: In addition to documentation Q&A, provides integration entry points for Web / Android / iOS / Flutter, including UI-based integration directions.
• Reliable source: Grounded in official Tencent Cloud materials to improve answer reliability and implementation readiness.
• Wide compatibility: Exposes MCP capabilities over STDIN/STDOUT JSON-RPC, compatible with MCP clients such as Cursor / Codex / Claude / CodeBuddy.
• Quick start: Run with npx and get started with minimal setup.

Requirements

• Node.js (>= 18) and npm
• An MCP-capable IDE

Usage

Standard setup flow

• Step1: In your Cursor project, create or edit .cursor/mcp.json or ~/.cursor/mcp.json and add the following configuration.

{
  "mcpServers": {
    "tencent-rtc": {
      "command": "npx",
      "args": ["-y", "@tencent-rtc/mcp@latest"],
      "env": {
        "SDKAPPID": "YOUR_SDKAPPID",
        "SECRETKEY": "YOUR_SECRET_KEY"
      }
    }
  }
}

After saving, a prompt appears. Click Enable in the prompt.

• Step2: Go to Cursor Settings (top-right gear icon) -> MCP, and make sure tencent-rtc is enabled.

• Step3: Describe your requirements directly in the IDE, and let the AI complete implementation or troubleshooting based on Tencent Cloud SDK documentation.

Optional: global install

If you want quick global invocation locally, run:

npx -y @tencent-rtc/mcp

Changelog

Only recent updates are listed here. For full history, see CHANGELOG.md.

Version 1.7.3 @2026.08.17

Added

• Added knowledge base resources for RoomKit multi-platform integration, recording, whiteboard, network proxy, AI noise reduction, and subtitle translation, expanding coverage of the Room product domain.
• Added best-practice docs covering error codes, log levels, automatic screen-share stop, and WeChat Mini Program error troubleshooting.
• Added a generic additive rerank module with anchor selection and phrase extraction, integrated into the search reranking logic to improve recall ranking accuracy.

Changed

• Optimized the BM25 index to use prototype-less objects, improving the isolation and stability of the index structure.

Fixed

• Fixed BM25 scoring anomalies caused by prototype-key pollution by adding prototype-key guards, preventing score pollution and NaN issues.

Version 1.7.1 @2026.08.11

Added

• Added pre-search normalization: normalizes product / frameworks based on prompt truth, fixing retrieval bias caused by wrong agent inference.

Changed

• Optimized the search_trtc_knowledge output contract: removed brevity wording such as "1-2 sentence per subsection", replaced with complete synthesized answers.

Fixed

• Fixed the case where mis-passed dual product / dual frameworks (e.g., "安卓 Web TRTC") were not corrected according to the prompt truth.

Version 1.7.0 @2026.08.02

Added

• Added and synchronized best-practice docs across product domains including Chat / Call / Live / Room to improve knowledge coverage.

Changed

• Continued refactoring of the bilingual retrieval pipeline, including query normalization, intent routing, candidate filtering, and exact-match strategies.
• Improved recall and ranking for best-practice and URL-based documents to increase answer usability and stability.
• Improved search_trtc_knowledge definitions and answer constraints for better readability and executability.

Fixed

• Fixed off-topic retrieval in some complex queries, reducing high-score false-positive hits.