Gitee▌
by normal-coder
Integrate with Gitee to manage repositories, track issues, and streamline code workflows easily using secure token authe
Integrates with Gitee repositories to enable repository creation, code management, issue tracking, and pull request workflows using a simple token-based authentication system.
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
best for
- / Developers automating Gitee repository management
- / Teams streamlining issue tracking workflows
- / AI-assisted code review and pull request handling
capabilities
- / Create and fork Gitee repositories
- / Manage branches and file operations
- / Create and update issues with comments
- / Handle pull request workflows
- / Push multiple files to repositories
- / List and retrieve repository details
what it does
Connects AI assistants to Gitee repositories for managing code, issues, and pull requests. Enables automated Git workflows through simple token authentication.
about
Gitee is a community-built MCP server published by normal-coder that provides AI assistants with tools and capabilities via the Model Context Protocol. Integrate with Gitee to manage repositories, track issues, and streamline code workflows easily using secure token authe It is categorized under developer tools, productivity.
how to install
You can install Gitee in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
license
MIT
Gitee is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
readme
Gitee MCP Server
Let AI operate Gitee repositories/Issues/Pull Requests for you through MCP
<img width="380" height="200" src="https://glama.ai/mcp/servers/cck9xigm1d/badge" />
Supported AI Operations
| Category | MCP Tool | Description |
|---|---|---|
| Repository Operations | create_repository | Create a Gitee repository |
fork_repository | Fork a Gitee repository | |
| Branch Operations | create_branch | Create a new branch in a Gitee repository |
list_branches | List branches in a Gitee repository | |
get_branch | Get details of a specific branch in a Gitee repository | |
| File Operations | get_file_contents | Get contents of a file or directory in a Gitee repository |
create_or_update_file | Create or update a file in a Gitee repository | |
push_files | Push multiple files to a Gitee repository | |
| Issue Operations | create_issue | Create an Issue in a Gitee repository |
list_issues | List Issues in a Gitee repository | |
get_issue | Get details of a specific Issue in a Gitee repository | |
update_issue | Update an Issue in a Gitee repository | |
add_issue_comment | Add a comment to an Issue in a Gitee repository | |
| Pull Request Operations | create_pull_request | Create a Pull Request in a Gitee repository |
list_pull_requests | List Pull Requests in a Gitee repository | |
get_pull_request | Get details of a specific Pull Request in a Gitee repository | |
update_pull_request | Update a Pull Request in a Gitee repository | |
merge_pull_request | Merge a Pull Request in a Gitee repository | |
| User Operations | get_user | Get Gitee user information |
get_current_user | Get authenticated Gitee user information |
Usage
Installing via Smithery
To install Gitee MCP Server for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @normal-coder/gitee-mcp-server --client claude
Configuration
GITEE_API_BASE_URL: Optional, Gitee OpenAPI Endpoint, default ishttps://gitee.com/api/v5GITEE_PERSONAL_ACCESS_TOKEN: Required, Gitee account personal access token (PAT), can be obtained from Gitee account settings Personal Access TokensDEBUG: Optional, set totrueto enable debug logging, default is disabled
Run MCP Server via NPX
{
"mcpServers": {
"Gitee": {
"command": "npx",
"args": [
"-y",
"gitee-mcp-server"
],
"env": {
"GITEE_PERSONAL_ACCESS_TOKEN": "<YOUR_TOKEN>"
}
}
}
}
Run MCP Server via Docker Container
- Get Docker Image
# Get from DockerHub
docker pull normalcoder/gitee-mcp-server
# Build locally
docker build -t normalcoder/gitee-mcp-server .
- Configure MCP Server
{
"mcpServers": {
"Gitee": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e",
"GITEE_PERSONAL_ACCESS_TOKEN",
"normalcoder/gitee-mcp-server"
],
"env": {
"GITEE_PERSONAL_ACCESS_TOKEN": "<YOUR_TOKEN>"
}
}
}
}
Development Guide
Install Dependencies
npm install
Build
npm run build
After successful build, /dist will contain the runnable MCP server.
Run Server
npm start
The MCP server will run on stdio, allowing it to be used as a subprocess by MCP clients.
Build Docker Image
You can also run the server using Docker:
docker build -t normalcoder/gitee-mcp-server .
Run MCP Server with Docker:
docker run -e GITEE_PERSONAL_ACCESS_TOKEN=<YOUR_TOKEN> normalcoder/gitee-mcp-server
Debug MCP Server
You can use @modelcontextprotocol/inspector for debugging:
Create a .env file in the root directory for environment variables:
GITEE_API_BASE_URL=https://gitee.com/api/v5
GITEE_PERSONAL_ACCESS_TOKEN=<YOUR_TOKEN>
Run the debug tool to start the service and web debug interface:
npx @modelcontextprotocol/inspector npm run start --env-file=.env
The project includes a debug() function for printing debug information, usage:
import { debug } from './common/utils.js';
debug('Message to log');
debug('Message with data:', { key: 'value' });
Debug logs are only printed when the DEBUG environment variable is set to true.
Dependencies
@modelcontextprotocol/sdk: MCP SDK for server implementationuniversal-user-agent: For generating user agent stringszod: For schema validationzod-to-json-schema: For converting Zod schemas to JSON schemas
License
Licensed under MIT License. You are free to use, modify and distribute the software, subject to the terms and conditions of the MIT License. For more details, see the LICENSE file in the project repository.
Related Links
FAQ
- What is the Gitee MCP server?
- Gitee is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
- How do MCP servers relate to agent skills?
- Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
- How are reviews shown for Gitee?
- This profile displays 28 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.8 out of 5—verify behavior in your own environment before production use.
Use Cases▌
Extended AI Capabilities
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Context Enhancement
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Workflow Automation
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Implementation Guide▌
Prerequisites
- ›Claude Desktop 0.7.0+ or Cursor IDE with MCP support
- ›Basic understanding of MCP architecture and capabilities
- ›Access credentials for integrated services (if required)
- ›Willingness to experiment and iterate on configuration
Time Estimate
15-60 minutes depending on server complexity
Installation Steps
- 1.Install MCP server: npm install -g [package-name] or via GitHub
- 2.Add server configuration to ~/.claude/mcp.json
- 3.Provide required credentials and configuration
- 4.Restart Claude Desktop to load new server
- 5.Test basic functionality with simple prompts
- 6.Explore capabilities and experiment with use cases
- 7.Document successful patterns for reuse
Troubleshooting
- ⚠MCP server not loading: Check config syntax, verify installation
- ⚠Connection errors: Check network, firewall, credentials
- ⚠Feature not working: Read server docs, check required parameters
- ⚠Performance issues: Monitor resource usage, check for network latency
- ⚠Conflicts with other servers: Check port assignments, namespace collisions
Best Practices▌
✓ Do
- +Read server documentation thoroughly before setup
- +Start with simple use cases to validate functionality
- +Test in non-production environment first
- +Monitor resource usage and performance
- +Keep servers updated for bug fixes and new features
- +Document configuration for team members
- +Use environment variables for sensitive configuration
✗ Don't
- −Don't grant overly permissive access to MCP servers
- −Don't skip reading security considerations in docs
- −Don't expose sensitive data without proper controls
- −Don't run untrusted MCP servers without code review
- −Don't ignore error messages—investigate root cause
💡 Pro Tips
- ★Combine multiple MCP servers for powerful workflows
- ★Create custom MCP servers for your specific needs
- ★Share successful configurations with team
- ★Use MCP inspector for debugging
- ★Join MCP community for tips and troubleshooting
Technical Details▌
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
- Model Context Protocol (MCP)
- JSON-RPC 2.0
- stdio or HTTP transport
Compatibility
- Claude Desktop
- Cursor IDE
- Custom MCP clients
When to Use This▌
✓ Use When
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid When
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.
Integration▌
- →Tool composition: Chain multiple MCP tools in workflows
- →Context augmentation: Provide AI with relevant external data
- →Action delegation: Let AI execute tasks on external systems
- →Bidirectional sync: Keep AI context and external systems in sync
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
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Ratings
4.8★★★★★28 reviews- ★★★★★Ganesh Mohane· Dec 24, 2024
Useful MCP listing: Gitee is the kind of server we cite when onboarding engineers to host + tool permissions.
- ★★★★★Camila Yang· Dec 8, 2024
We evaluated Gitee against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Isabella Singh· Dec 8, 2024
Gitee has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
- ★★★★★Ira Ghosh· Nov 27, 2024
Useful MCP listing: Gitee is the kind of server we cite when onboarding engineers to host + tool permissions.
- ★★★★★Isabella Zhang· Nov 27, 2024
According to our notes, Gitee benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Yash Thakker· Nov 23, 2024
Gitee reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Sakshi Patil· Nov 15, 2024
We evaluated Gitee against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Liam Martinez· Oct 18, 2024
Strong directory entry: Gitee surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★Nia Farah· Oct 18, 2024
Gitee is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Dhruvi Jain· Oct 14, 2024
We wired Gitee into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
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