Skip to main content
AllMCPs
BrowseBestCategoriesStackCompareToolsGuidesBlog
Log in Submit MCP

Stay in the loop

Get new MCP servers and top picks in your inbox.

AllMCPs

The open directory for discovering and installing Model Context Protocol servers.

AllMCPs on GitHub (opens in a new tab)
Launched onTiny Startupstinystartups.com
Explore
  • Browse servers
  • Best MCP servers
  • Categories
  • MCP clients
  • Agent prompts
  • Stack Builder
  • Compare servers
  • Random discovery New
  • Submit a server
  • Pricing & Boost Boost
Learn
  • Guides hub
  • What is MCP?
  • Install guide
  • Build an MCP server
  • Deploy an MCP server
  • Security guide
  • Troubleshooting
  • MCP for SEO & AEO
  • Protocol versioning
  • Blog & updates
Tools
  • All developer tools
  • Config generator
  • Config validator
  • Config auditor
  • MCP playground
  • Token calculator
  • OpenAPI → MCP
  • Badge generator
For agents
  • REST API docs
  • Trust & traffic Live
  • Remote MCP server SSE ↗ (opens in a new tab)
  • llms.txt ↗ (opens in a new tab)
  • Catalog JSON ↗ (opens in a new tab)
Company
  • About
  • Advertise Sponsor
  • Contact
  • GitHub ↗ (opens in a new tab)
  • Terms
  • Privacy
AllMCPs VerifiedAllMCPs VerifiedFeatured on Nick LaunchesFeatured on Nick LaunchesLaunch Llama NewsletterLaunch Llama NewsletterVerified DR - allmcps.comVerified DR - allmcps.comFeatured on SaaSGrowFeatured on SaaSGrowFeatured on Twelve ToolsFeatured on Twelve ToolsFeatured on Saaspa.geFeatured on Saaspa.geFeatured on Findly.toolsFeatured on Findly.toolsFeatured on Startup FameFeatured on Startup FameFeatured on LaunchKiwiFeatured on LaunchKiwiFeatured on ScrollLaunchFeatured on ScrollLaunchFeatured on DailyPingsFeatured on DailyPingsFazier badgeFazier badgeFeatured on NewTool.siteFeatured on NewTool.siteFeatured on saasfame.comFeatured on saasfame.comDR Checker - Domain RatingDR Checker - Domain RatingListed on Turbo0Listed on Turbo0Launched on LaunchBoard - Product Launch PlatformLaunched on LaunchBoard - Product Launch PlatformList on SimilarlabsList on Similarlabshttps://codetrendy.comhttps://codetrendy.comListed on DevTool.ioFeatured on BuildlistFeatured on BuildlistLaunched on Tiny StartupsFeatured on ShowMeBestAIFeatured on ShowMeBestAIFind us on LaunchZoneFind us on LaunchZoneAllMCPs VerifiedAllMCPs VerifiedFeatured on Nick LaunchesFeatured on Nick LaunchesLaunch Llama NewsletterLaunch Llama NewsletterVerified DR - allmcps.comVerified DR - allmcps.comFeatured on SaaSGrowFeatured on SaaSGrowFeatured on Twelve ToolsFeatured on Twelve ToolsFeatured on Saaspa.geFeatured on Saaspa.geFeatured on Findly.toolsFeatured on Findly.toolsFeatured on Startup FameFeatured on Startup FameFeatured on LaunchKiwiFeatured on LaunchKiwiFeatured on ScrollLaunchFeatured on ScrollLaunchFeatured on DailyPingsFeatured on DailyPingsFazier badgeFazier badgeFeatured on NewTool.siteFeatured on NewTool.siteFeatured on saasfame.comFeatured on saasfame.comDR Checker - Domain RatingDR Checker - Domain RatingListed on Turbo0Listed on Turbo0Launched on LaunchBoard - Product Launch PlatformLaunched on LaunchBoard - Product Launch PlatformList on SimilarlabsList on Similarlabshttps://codetrendy.comhttps://codetrendy.comListed on DevTool.ioFeatured on BuildlistFeatured on BuildlistLaunched on Tiny StartupsFeatured on ShowMeBestAIFeatured on ShowMeBestAIFind us on LaunchZoneFind us on LaunchZone
© 2026 Jackalope Digital LLC. All rights reserved.
  1. Home
  2. Coding Agents
  3. MCP Creator Growth
  4. README

MCP Creator Growth README

The full upstream README, mirrored here for reference. Install config, tool schemas, adoption signals, and an original overview live on the MCP Creator Growth listing page.

Back to MCP Creator Growth View source on GitHub

Covate

English | 简体中文 | 繁體中文

A context-aware Model Context Protocol (MCP) server that acts as a learning sidecar for AI coding assistants. It helps developers learn from AI-generated code changes through interactive quizzes and provides agents with a persistent project-specific debugging memory.

License: MIT Python 3.11+ MCP Standard Docker Glama MCP DeepWiki


🌐 Resources

ResourceDescription
Glama MCP MarketplaceOfficial MCP server listing with installation guides
DeepWiki DocumentationAI-generated deep analysis of the codebase
GitHub RepositorySource code, issues, and contributions

🚀 Why Use This?

ForBenefit
DevelopersDon't just accept AI code—understand it. Request a quiz to verify your grasp of the logic, security, or performance implications.
AI AgentsStop solving the same bug twice. The server quietly records debugging solutions and retrieves them automatically when similar errors occur.

☁️ Covate learning ledger (free)

The MCP server in this repo is free and open-source (MIT) — run it locally, no account required. The optional hosted learning ledger is free too: sign in with GitHub, then run COVATE_SYNC_URL=https://covate.org COVATE_SYNC_TOKEN=<your token> python -m covate.platform_sync from a project to push your local sessions up and review them in a browser:

  • ☁️ Sync your learning sessions from any machine
  • 📖 Every synced session, newest first, with its score
  • 📊 Totals — sessions, questions, correct answers, running accuracy
  • 🎯 The topics you answer worst, ranked
  • 🔑 Your sync token — reveal or rotate it whenever you want

Not built yet, so not promised: progress-over-time charts, spaced-repetition study plans, team accounts. There is no paid tier and nothing to buy — the MCP works fully without the ledger, and the ledger costs nothing.


📦 Available Tools

ToolTypeDescription
learning_session🎓 InteractiveOpens a WebUI quiz based on recent code changes. Blocks until user completes learning.
debug_search🔍 Silent RAGSearches project debug history for relevant past solutions. Auto-triggered on errors.
debug_record📝 SilentRecords debugging experiences to project knowledge base. Auto-triggered after fixes.
term_get📚 ReferenceFetches programming terms/concepts. Tracks shown terms to avoid repetition.

Tool Details

🎓 learning_session - Interactive Learning Card

Trigger: User explicitly requests (e.g., "Quiz me", "Test my understanding")

Parameters:

ParameterTypeDefaultDescription
project_directorystring"."Project directory path
summarystring—Structured summary of Agent's actions
reasoningobjectnull5-Why reasoning (goal, trigger, mechanism, alternatives, risks)
quizzesarrayauto-generated3 quiz questions with options, answer, explanation
focus_areasarray["logic"]Focus areas: logic, security, performance, architecture, syntax
timeoutint600Timeout in seconds (60-7200)

Returns: {"status": "completed", "action": "HALT_GENERATION"}

🔍 debug_search - Search Debug History

Trigger: Auto-called when encountering errors (silent, no UI)

Parameters:

ParameterTypeDefaultDescription
querystring—Error message or description to search
project_directorystring"."Project directory path
error_typestringnullFilter by error type (e.g., ImportError)
tagsarraynullFilter by tags
limitint5Maximum results (1-20)

Returns: {"results": [...], "count": N}

📝 debug_record - Record Debug Experience

Trigger: Auto-called after fixing bugs (silent, background)

Parameters:

ParameterTypeDefaultDescription
contextobject—Error context: {error_type, error_message, file, line}
causestring—Root cause analysis
solutionstring—Solution that worked
project_directorystring"."Project directory path
tagsarraynullTags for categorization

Returns: {"ok": true, "id": "..."}

📚 term_get - Get Programming Terms

Available Domains: programming_basics, data_structures, algorithms, software_design, web_development, version_control, testing, security, databases, devops

Parameters:

ParameterTypeDefaultDescription
project_directorystring"."Project directory path
countint3Number of terms (1-5)
domainstringnullFilter by domain

Returns: {"terms": [...], "count": N, "remaining": N}


🛠️ Installation

One-Line Install (Recommended)

PlatformCommand
macOS / Linux
Terminal
curl -fsSL https://raw.githubusercontent.com/SunflowersLwtech/covate/main/scripts/install.sh | bash
Windows (PowerShell)
powershell
irm https://raw.githubusercontent.com/SunflowersLwtech/covate/main/scripts/install.ps1 | iex

The installer will:

  1. Auto-detect your Python environment (uv → conda → venv)
  2. Clone the repository to ~/covate
  3. Create virtual environment and install dependencies
  4. Print the exact command to configure your IDE

Manual Installation

Click to expand manual installation steps

Prerequisites: Python 3.11+ or uv

bash
# 1. Clone the repository
git clone https://github.com/SunflowersLwtech/covate.git
cd covate

# 2. Create virtual environment and install
# Using uv (recommended)
uv venv --python 3.11 covate
source covate/bin/activate          # macOS/Linux
# covate\Scripts\activate           # Windows
uv pip install -e '.[dev]'

# Or using standard venv
python -m venv covate
source covate/bin/activate           # macOS/Linux
# covate\Scripts\activate            # Windows
pip install -e '.[dev]'

Docker Installation

Click to expand Docker installation steps

Prerequisites: Docker installed on your system

bash
# 1. Pull from Docker Hub
docker pull sunflowerslwtech/covate:latest

# Or build locally
git clone https://github.com/SunflowersLwtech/covate.git
cd covate
docker build -t covate .

# 2. Run with Docker
docker run -i covate

# 3. Or use Docker Compose
docker-compose up -d

For detailed Docker usage, persistent storage, and Claude Desktop integration, see DOCKER.md.


⚙️ IDE Configuration

Claude Code (CLI) — One Command Setup

After installation, configure your AI coding IDE to use this MCP server.

Claude Code

Option 1: CLI (Recommended)

bash
# macOS / Linux
claude mcp add covate -- ~/covate/covate/bin/covate

# Windows
claude mcp add covate -- %USERPROFILE%\covate\covate\Scripts\covate.exe

Option 2: Config File

Add to ~/.claude.json:

config.json
{
  "mcpServers": {
    "covate": {
      "command": "~/covate/covate/bin/covate"
    }
  }
}

For Windows:

config.json
{
  "mcpServers": {
    "covate": {
      "command": "C:\\Users\\YourName\\covate\\covate\\Scripts\\covate.exe"
    }
  }
}

Example paths:

  • Unix (uv): ~/covate/covate/bin/covate
  • Windows (uv): C:\\Users\\YourName\\covate\\covate\\Scripts\\covate.exe
  • Windows (conda): C:\\Users\\YourName\\anaconda3\\envs\\covate\\Scripts\\covate.exe

Path breakdown (Unix example):

  • ~/covate → repository directory
  • covate → virtual environment directory created by uv/venv
  • bin/covate → executable

Cursor

Add to Cursor MCP settings (Settings → MCP → Add Server):

config.json
{
  "covate": {
    "command": "~/covate/covate/bin/covate"
  }
}

For Windows:

config.json
{
  "covate": {
    "command": "C:\\Users\\YourName\\covate\\covate\\Scripts\\covate.exe"
  }
}

Windsurf

Add to ~/.codeium/windsurf/mcp_config.json:

config.json
{
  "mcpServers": {
    "covate": {
      "command": "~/covate/covate/bin/covate"
    }
  }
}

Docker Configuration

To use Docker with any MCP-compatible IDE:

config.json
{
  "mcpServers": {
    "covate": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-v",
        "/path/to/your/project:/workspace",
        "-w",
        "/workspace",
        "covate"
      ]
    }
  }
}

See DOCKER.md for detailed Docker configuration examples for Claude Desktop, Cursor, and other IDEs.

Other IDEs

For any MCP-compatible IDE, use these settings:

  • Command: <install-path>/covate/bin/covate (or covate\Scripts\covate.exe on Windows)
  • Transport: stdio

After configuration, restart your IDE.

Usage

Available Tools

ToolTriggerForReturns
learning_sessionUser explicit requestUser{status, action} - minimal
debug_searchAutomatic (on error)AgentCompact summaries
debug_recordAutomatic (after fix)Agent{ok, id} - minimal

For Users: Learning Session

Say to your AI assistant:

  • "Quiz me on this change"
  • "Test my understanding"
  • "Help me learn about what you did"

The agent will create an interactive learning card and wait until you complete it.

Note: Quiz scores are saved locally for your self-tracking but are NOT returned to the agent - this keeps the context clean.

For Agents: Debug Tools

The debug tools work silently in the background:

  • Search first: When encountering errors, agent searches past solutions
  • Record after: When fixing errors, agent records the solution
  • Progressive disclosure: Returns compact summaries, not full records
  • Fast lookups: Uses inverted index for keyword-based searches

Updating

One-Line Update (Recommended)

The remote update script automatically detects your installation and works with any path format (including Chinese/non-ASCII paths):

macOS / Linux
Terminal
curl -fsSL https://raw.githubusercontent.com/SunflowersLwtech/covate/main/scripts/update.sh | bash
Windows (PowerShell)
powershell
irm https://raw.githubusercontent.com/SunflowersLwtech/covate/main/scripts/update.ps1 | iex

The update script will:

  1. Auto-detect your installation location (supports multiple installations)
  2. Pull the latest changes from the repository
  3. Force-reinstall dependencies to ensure version synchronization
  4. Verify installation integrity and report any issues
  5. Detect if MCP server is in use and provide clear instructions

Why remote update?

  • ✅ Works with Chinese/non-ASCII paths without cd navigation
  • ✅ Always uses the latest update logic from the repository
  • ✅ Auto-detects installation location even if you forgot where it is
  • ✅ Handles multiple installations gracefully

Local Update (Alternative)

macOS / Linux:

bash
~/covate/scripts/update.sh

Windows (PowerShell):

powershell
~\covate\scripts\update.ps1

Manual Update

Click to expand manual update steps
bash
# Navigate to installation directory
cd ~/covate  # or your custom installation path

# Pull latest changes
git pull origin main

# Update dependencies
# Using uv
source covate/bin/activate          # macOS/Linux
# covate\Scripts\activate           # Windows
uv pip install -e '.[dev]' --upgrade

# Or using standard venv
source covate/bin/activate           # macOS/Linux
# covate\Scripts\activate            # Windows
pip install -e '.[dev]' --upgrade

🖼️ Screenshots

Learning Session WebUI

WebUI Preview


🔒 Security & Privacy

AspectDetails
Local FirstAll data stored in .mcp-sidecar/ directory within your project
No TelemetryZero data sent to external servers
Full ControlDelete .mcp-sidecar/ anytime to reset all data

🔮 Roadmap

We're building toward a Personalized Learning Center that grows with you. Here's what's coming:

🔍 Advanced Search & Indexing (v1.2)

FeatureDescription
SQLite FTS5Full-text search with Chinese support, prefix matching, and boolean queries
BM25 RankingIndustry-standard relevance scoring for better search results
Semantic SearchVector embeddings for meaning-based matching (e.g., "权限错误" finds "permission denied")
Cross-project SearchSearch debug experiences across all your projects

📱 Mobile App (v2.0)

FeatureDescription
Learning History SyncAccess your quiz history and learning progress on mobile
Spaced RepetitionSmart review scheduling based on forgetting curves
Offline ModeLearn anywhere, sync when connected
Push NotificationsGentle reminders to review concepts you're forgetting

🎯 Personalized Learning Center (v2.5)

FeatureDescription
Knowledge GraphVisual map of concepts you've learned and their connections
Weakness AnalysisAI identifies areas where you struggle and suggests focused practice
Learning StreaksGamification to keep you motivated
Team Insights(Optional) Share anonymized learning patterns with your team

🤖 AI Enhancements (v3.0)

FeatureDescription
Adaptive QuizzesQuestions adjust difficulty based on your performance
Code Pattern RecognitionLearn from patterns in your own codebase
Multi-language SupportExplanations in your preferred language
Voice Interface"Hey Claude, quiz me on what we did yesterday"

Want to influence the roadmap? Open an issue or join the discussion!


🔧 Environment Variables

VariableDefaultDescription
MCP_DEBUGfalseEnable debug logging (true, 1, yes, on)
MCP_TIMEOUT120000MCP server startup timeout in ms
MAX_MCP_OUTPUT_TOKENS25000Maximum tokens for MCP output

🤝 Contributing

We welcome contributions! Please follow these steps:

  1. Fork the repository
  2. Create a feature branch: git checkout -b feature/amazing-feature
  3. Install dev dependencies: uv pip install -e '.[dev]'
  4. Make changes and run tests: pytest
  5. Submit a Pull Request

See CONTRIBUTING.md for detailed guidelines.


📬 Contact

ChannelAddress
Emailsunflowers0607@outlook.com
Emailweiliu0607@gmail.com
GitHub IssuesOpen an Issue

📄 License

This project is licensed under the MIT License.


Built with FastMCP • MCP Standard • Glama MCP