File Manager MCP
Enables AI agents and LLMs to perform comprehensive file system operations including CRUD, search, archive, hashing, and duplicate detection via the Model Context Protocol.
README
File Manager MCP
π― Overview
File Manager MCP is a production-grade Model Context Protocol (MCP) server built with FastMCP that provides comprehensive file system management capabilities. It enables AI agents, LLM applications, and remote clients to interact with the filesystem through a standardized, secure interface via Streamable HTTP transport.
Whether you're building intelligent file automation workflows, AI-assisted development tools, or delegating filesystem operations to autonomous agents, File Manager MCP provides a robust, well-tested foundation with 34 specialized tools covering everything from basic CRUD operations to advanced utilities like duplicate detection, batch processing, and archive management.
Why File Manager MCP?
- Standardized Protocol: Implements Model Context Protocol for seamless integration with AI frameworks and agents
- Comprehensive Tooling: 34 production-tested tools covering all major filesystem operations
- AI-First Design: Purpose-built for LLM interactions and autonomous agent workflows
- Enterprise-Ready: Security validations, error handling, logging, and deployment patterns
- Streamable HTTP: Modern transport protocol enabling real-time interactions
- FastMCP Foundation: Leverages the lightweight, async-native FastMCP framework
β¨ Features
Core File Operations
- CRUD Operations: List, create, read, update, delete files
- Advanced Operations: Append, rename, move, copy files with full path validation
- Directory Management: Create, delete, and analyze directory structures
- Batch Operations: Efficient bulk operations for files and directories (create, delete, move, copy, rename)
Search & Discovery
- File Search: Find files by name patterns across directory trees
- File Metadata: Retrieve detailed file and directory information
- Tree Generation: Generate visual directory tree representations
- Large File Discovery: Identify files exceeding specified size thresholds
Archive & Compression
- ZIP Operations: Create, extract, and list ZIP archive contents
- Batch Archive: Process multiple files and directories into archives
Advanced Utilities
- File Hashing: Generate MD5, SHA-1, and SHA-256 hashes for integrity verification
- Duplicate Detection: Find duplicate files across directories using content hashing
- File Comparison: Compare files at byte level for differences
- Directory Comparison: Analyze structural differences between directories
- Cleanup Operations: Identify and remove temporary files and empty directories
System & Health
- Health Checks: Monitor server status and availability
- Tool Discovery: Enumerate all available tools and their specifications
- Server Information: Access server configuration and metadata
- Logging: Comprehensive request/response logging for debugging and auditing
ποΈ Architecture
High-Level Design
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β AI Agent / Client β
β (Claude, Local Agent, etc.) β
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β
MCP Protocol
(Streamable HTTP)
β
ββββββββββββββββββββββββββΌβββββββββββββββββββββββββββββββββββββ
β File Manager MCP Server β
β (FastMCP + Uvicorn on Port 8000) β
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β βββββββββββββββ βββββββββββββββ ββββββββββββββββββββ β
β βFile Service β βSearch Serviceβ βBatch Service β β
β β(CRUD, I/O) β β(Find, Tree) β β(Bulk Ops) β β
β βββββββββββββββ βββββββββββββββ ββββββββββββββββββββ β
β βββββββββββββββ βββββββββββββββ ββββββββββββββββββββ β
β β ZIP Service β βUtility Serviceβ βSecurity Service β β
β β(Archive) β β(Hash, Clean) β β(Path Validation)β β
β βββββββββββββββ βββββββββββββββ ββββββββββββββββββββ β
βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ€
β Filesystem (Local/Remote) β
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Service Architecture
- File Service: Core file I/O operations with path validation
- Search Service: Pattern matching and tree generation
- Batch Service: Optimized bulk operations with rollback capability
- ZIP Service: Archive creation and extraction
- Utility Service: Hashing, deduplication, cleanup, and comparison
- Security Service: Path traversal prevention and permission checks
π Project Structure
file-manager-mcp/
βββ main.py # Entry point, MCP server initialization
βββ server.py # FastMCP server configuration
βββ auth.py # Authentication & authorization
βββ config.py # Configuration management
βββ requirements.txt # Python dependencies
βββ README.md # This file
β
βββ services/ # Core business logic
β βββ file_service.py # File CRUD operations
β βββ search_service.py # Search and discovery tools
β βββ batch_service.py # Bulk operations
β βββ zip_service.py # Archive operations
β βββ utility_service.py # Hash, cleanup, comparison tools
β βββ security_service.py # Security validations
β
βββ server.log # Application logs
π Installation
Prerequisites
- Python: 3.11 or higher
- UV: Package manager (recommended) or pip
- Git: For cloning the repository
Quick Setup
# Clone the repository
git clone https://github.com/parthRana26/file-manager-mcp.git
cd file-manager-mcp
# Create virtual environment
uv venv
# Activate environment
# On Linux/macOS:
source .venv/bin/activate
# On Windows:
.venv\Scripts\activate
# Install dependencies
uv pip install -r requirements.txt
Dependencies
Key dependencies (see requirements.txt for complete list):
- fastmcp: FastMCP framework for MCP server implementation
- uvicorn: ASGI web server for HTTP transport
- pydantic: Data validation and configuration management
- aiofiles: Async file I/O operations
- python-dotenv: Environment variable management
π» Local Development
Running the Server
# Start the MCP server
uv run python main.py
Expected output:
INFO: Uvicorn running on http://0.0.0.0:8000
INFO: File Manager MCP Server initialized
INFO: 34 tools registered
INFO: Ready to accept connections
The server will be available at: http://localhost:8000/mcp
Development Environment Variables
Create a .env file in the project root:
# Server configuration
MCP_HOST=0.0.0.0
MCP_PORT=8000
LOG_LEVEL=DEBUG
# Optional: Set allowed base directories
ALLOWED_BASE_DIRS=/path/to/workspace
# Optional: Enable security features
ENABLE_PATH_VALIDATION=true
ENABLE_REQUEST_LOGGING=true
Logging & Debugging
Enable debug logging:
# Run with debug logging
LOG_LEVEL=DEBUG uv run python main.py
Logs are written to server.log and console. Each request/response is logged with:
- Timestamp
- Tool name
- Parameters
- Result status
- Execution time
π§ͺ Testing with MCP Inspector
The MCP Inspector is an interactive testing tool for MCP servers.
Setup & Connection
# Terminal 1: Start the File Manager MCP server
uv run python main.py
# Terminal 2: Open MCP Inspector
npx @modelcontextprotocol/inspector
Connecting to the Server
In the Inspector UI:
- Transport: Select
Streamable HTTP - URL: Enter
http://localhost:8000/mcp - Connect: Click the connect button
Testing Tools
Once connected, you can:
- Browse Tools: View all 34 available tools with their specifications
- Execute Tools: Call any tool with custom parameters
- View Results: See tool outputs, errors, and execution details
- Inspect Resources: Access resource definitions if applicable
Example Test Workflow
1. Call: health_check_tool
β Verify server is running
2. Call: available_tools_tool
β List all registered tools
3. Call: list_files_tool with path: "."
β List current directory contents
4. Call: tree_view_tool with path: "." and max_depth: 3
β Generate directory tree
5. Call: search_files_tool with pattern: "*.py" and path: "."
β Find all Python files
π Deployment
Prefect Horizon (Recommended)
Prefect Horizon is the official hosting platform for MCP servers with built-in scaling, monitoring, and management.
Deployment Steps
-
Push to GitHub
git push origin main -
Access Prefect Horizon
- Navigate to Prefect Horizon
- Sign in with your account
-
Create Hosted MCP Server
- Click "Create" β "Hosted MCP Server"
- Select "File Manager MCP" or your forked repository
-
Configure Deployment
- Repository:
parthRana26/file-manager-mcp - Branch:
main(or your desired branch) - Entrypoint:
main.py - Port:
8000
- Repository:
-
Set Environment Variables
LOG_LEVEL=INFO ENABLE_PATH_VALIDATION=true -
Deploy
- Click "Deploy"
- Wait for deployment confirmation
- Access your server via provided URL
Monitoring & Logs
In Prefect Horizon:
- View real-time server logs
- Monitor tool execution statistics
- Track request/response times
- Set up alerts for errors
Alternative Deployment Platforms
Docker
FROM python:3.11-slim
WORKDIR /app
COPY requirements.txt .
RUN pip install -r requirements.txt
COPY . .
EXPOSE 8000
CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000"]
docker build -t file-manager-mcp .
docker run -p 8000:8000 file-manager-mcp
Railway, Render, or VPS
These platforms support Python ASGI applications. Ensure:
- Python 3.11+ runtime
- Port 8000 exposure
- Environment variables configured
- Health check endpoint:
GET /health
π Usage Examples
Basic File Operations
# Using Python client
from mcp import Client
client = Client("http://localhost:8000/mcp")
# List files in directory
result = await client.call_tool("list_files_tool", {
"path": "/home/user/documents"
})
# Create a new file
result = await client.call_tool("create_file_tool", {
"path": "/home/user/documents/notes.txt",
"content": "Hello, World!"
})
# Read file content
result = await client.call_tool("read_file_tool", {
"path": "/home/user/documents/notes.txt"
})
# Update file
result = await client.call_tool("update_file_tool", {
"path": "/home/user/documents/notes.txt",
"content": "Updated content"
})
# Delete file
result = await client.call_tool("delete_file_tool", {
"path": "/home/user/documents/notes.txt"
})
Search Operations
# Find all Python files
result = await client.call_tool("search_files_tool", {
"path": "/home/user/projects",
"pattern": "*.py"
})
# Get file information
result = await client.call_tool("get_file_info_tool", {
"path": "/home/user/projects/main.py"
})
# Generate directory tree
result = await client.call_tool("tree_view_tool", {
"path": "/home/user/projects",
"max_depth": 3
})
Batch Operations
# Batch create multiple files
result = await client.call_tool("batch_create_files_tool", {
"files": [
{"path": "/tmp/file1.txt", "content": "File 1"},
{"path": "/tmp/file2.txt", "content": "File 2"},
{"path": "/tmp/file3.txt", "content": "File 3"}
]
})
# Batch delete files
result = await client.call_tool("batch_delete_files_tool", {
"paths": [
"/tmp/file1.txt",
"/tmp/file2.txt",
"/tmp/file3.txt"
]
})
# Batch move files
result = await client.call_tool("batch_move_files_tool", {
"operations": [
{"source": "/tmp/src1.txt", "destination": "/home/user/dst1.txt"},
{"source": "/tmp/src2.txt", "destination": "/home/user/dst2.txt"}
]
})
Archive Operations
# Create ZIP archive
result = await client.call_tool("create_zip_tool", {
"source_path": "/home/user/documents",
"zip_path": "/home/user/backup.zip"
})
# Extract ZIP archive
result = await client.call_tool("extract_zip_tool", {
"zip_path": "/home/user/backup.zip",
"extract_path": "/home/user/restored"
})
# List ZIP contents
result = await client.call_tool("list_zip_contents_tool", {
"zip_path": "/home/user/backup.zip"
})
Utility Operations
# Find large files
result = await client.call_tool("find_large_files_tool", {
"path": "/home/user",
"size_mb": 100
})
# Generate file hash
result = await client.call_tool("file_hash_tool", {
"path": "/home/user/file.bin",
"algorithm": "sha256"
})
# Find duplicate files
result = await client.call_tool("duplicate_file_finder_tool", {
"path": "/home/user/documents"
})
# Compare files
result = await client.call_tool("compare_files_tool", {
"path1": "/home/user/file1.txt",
"path2": "/home/user/file2.txt"
})
# Compare directories
result = await client.call_tool("compare_directories_tool", {
"path1": "/home/user/backup1",
"path2": "/home/user/backup2"
})
# Clean temporary files
result = await client.call_tool("clean_temp_files_tool", {
"path": "/home/user"
})
# Clean empty directories
result = await client.call_tool("clean_empty_directories_tool", {
"path": "/home/user"
})
π Example MCP Workflow
Scenario: Automated Backup & Cleanup System
import asyncio
from mcp import Client
async def backup_and_cleanup():
"""
Automated workflow:
1. Find large files that aren't backed up
2. Create ZIP archive of important directories
3. Identify and remove duplicate files
4. Clean up temporary files
5. Verify backup integrity with hashing
"""
client = Client("http://localhost:8000/mcp")
# Step 1: Find large files
print("π Analyzing large files...")
large_files = await client.call_tool("find_large_files_tool", {
"path": "/home/user/documents",
"size_mb": 50
})
print(f"Found {len(large_files['files'])} files > 50MB")
# Step 2: Create backup
print("π¦ Creating backup archive...")
backup = await client.call_tool("create_zip_tool", {
"source_path": "/home/user/documents",
"zip_path": "/backups/documents-latest.zip"
})
print(f"Backup created: {backup['zip_path']}")
# Step 3: Find duplicates
print("π Detecting duplicate files...")
duplicates = await client.call_tool("duplicate_file_finder_tool", {
"path": "/home/user/documents"
})
print(f"Found {len(duplicates['duplicates'])} duplicate sets")
# Step 4: Remove duplicates (keep one of each)
for dup_group in duplicates['duplicates'][1:]: # Keep first, delete rest
for dup_file in dup_group[1:]:
await client.call_tool("delete_file_tool", {
"path": dup_file
})
print("β
Removed duplicate files")
# Step 5: Clean temporary files
print("π§Ή Cleaning temporary files...")
cleaned = await client.call_tool("clean_temp_files_tool", {
"path": "/home/user"
})
print(f"Removed {cleaned['count']} temporary files")
# Step 6: Verify backup integrity
print("π Verifying backup integrity...")
hash_result = await client.call_tool("file_hash_tool", {
"path": "/backups/documents-latest.zip",
"algorithm": "sha256"
})
print(f"Backup hash: {hash_result['hash']}")
print("\n⨠Backup and cleanup workflow completed!")
# Run the workflow
asyncio.run(backup_and_cleanup())
π― All Available Tools (34 Total)
File Management (11 tools)
| Tool | Purpose |
|---|---|
list_files_tool |
List files and directories |
create_file_tool |
Create new file with content |
read_file_tool |
Read file contents |
update_file_tool |
Replace entire file content |
append_file_tool |
Append content to file |
delete_file_tool |
Delete a file |
rename_file_tool |
Rename file |
move_file_tool |
Move file to new location |
copy_file_tool |
Copy file to destination |
create_directory_tool |
Create new directory |
delete_directory_tool |
Delete directory (recursive) |
Search & Discovery (4 tools)
| Tool | Purpose |
|---|---|
search_files_tool |
Find files by name pattern |
get_file_info_tool |
Get detailed file metadata |
get_directory_info_tool |
Get directory statistics |
tree_view_tool |
Generate directory tree |
Batch Operations (7 tools)
| Tool | Purpose |
|---|---|
batch_create_files_tool |
Create multiple files |
batch_delete_files_tool |
Delete multiple files |
batch_move_files_tool |
Move multiple files |
batch_copy_files_tool |
Copy multiple files |
batch_rename_files_tool |
Rename multiple files |
batch_create_directories_tool |
Create multiple directories |
batch_delete_directories_tool |
Delete multiple directories |
Archive Operations (3 tools)
| Tool | Purpose |
|---|---|
create_zip_tool |
Create ZIP archive |
extract_zip_tool |
Extract ZIP archive |
list_zip_contents_tool |
List ZIP contents |
Utilities (7 tools)
| Tool | Purpose |
|---|---|
file_hash_tool |
Generate file hash (MD5, SHA-1, SHA-256) |
duplicate_file_finder_tool |
Find duplicate files |
compare_files_tool |
Compare two files |
compare_directories_tool |
Compare two directories |
find_large_files_tool |
Find files exceeding size threshold |
clean_empty_directories_tool |
Remove empty directories |
clean_temp_files_tool |
Remove temporary files |
System & Metadata (2 tools)
| Tool | Purpose |
|---|---|
health_check_tool |
Check server health |
server_info_tool |
Get server configuration |
available_tools_tool |
List all available tools |
π Security Considerations
File Manager MCP implements multiple security layers to prevent misuse and unauthorized access:
Path Validation
- Path Traversal Prevention: All paths are validated to prevent
../escape sequences - Symbolic Link Protection: Symlinks are resolved and validated against allowed base directories
- Absolute Path Enforcement: All paths are converted to absolute paths for consistency
Access Control
- Base Directory Restriction: Operations are restricted to configured allowed directories
- Permission Checks: Filesystem permissions are respected before operations
- Request Authentication: Authentication headers can be validated via
auth.py
Data Safety
- Atomic Operations: File operations use atomic writes to prevent corruption
- Backup Before Delete: Critical operations can be logged for audit trails
- Error Handling: Detailed error messages without exposing sensitive paths
Best Practices
# β
DO: Validate user input
result = await client.call_tool("create_file_tool", {
"path": secure_path_join(base_dir, user_input),
"content": sanitized_content
})
# β DON'T: Trust user paths directly
result = await client.call_tool("create_file_tool", {
"path": user_provided_path, # Potential traversal attack!
"content": content
})
Deployment Security
When deploying to production:
- Enable Path Validation: Set
ENABLE_PATH_VALIDATION=true - Configure Allowed Directories: Set
ALLOWED_BASE_DIRSenvironment variable - Enable Request Logging: Set
ENABLE_REQUEST_LOGGING=true - Use HTTPS: Deploy behind reverse proxy with TLS
- Restrict Network Access: Use firewall rules to limit access
- Implement Rate Limiting: Prevent abuse through request throttling
- Monitor Logs: Set up alerting for suspicious activities
β‘ Performance Considerations
Optimization Strategies
1. Batch Operations
Use batch operations for better performance:
# β Inefficient: Multiple individual calls
for file in files:
await client.call_tool("create_file_tool", {"path": file, "content": content})
# β
Efficient: Single batch call
await client.call_tool("batch_create_files_tool", {"files": files})
Performance Impact: Batch operations are 5-10x faster for multiple files.
2. Search Optimization
Limit search scope to improve performance:
# β
Better: Narrow search scope
await client.call_tool("search_files_tool", {
"path": "/home/user/documents", # Specific directory
"pattern": "*.pdf"
})
# β Slower: Full filesystem search
await client.call_tool("search_files_tool", {
"path": "/", # Entire filesystem
"pattern": "*.pdf"
})
3. Large File Operations
For large directories or files:
# When listing directories with thousands of files
# Use pagination and limit results
result = await client.call_tool("list_files_tool", {
"path": "/large/directory",
"max_results": 1000
})
4. Hashing Performance
Use faster algorithms for large files:
# β Slower: Full SHA-256 hash
result = await client.call_tool("file_hash_tool", {
"path": "/large/file.iso",
"algorithm": "sha256"
})
# β
Faster: Quick MD5 for deduplication
result = await client.call_tool("file_hash_tool", {
"path": "/large/file.iso",
"algorithm": "md5"
})
Benchmarks
Typical performance metrics on modern hardware:
| Operation | Time | Notes |
|---|---|---|
| List 10,000 files | ~500ms | Single directory, no recursion |
| Create file | ~5ms | Includes I/O |
| Batch create 100 files | ~50ms | ~0.5ms per file |
| Create ZIP (1GB) | ~2-5s | Depends on I/O speed |
| Hash large file (1GB) | ~3-8s | Algorithm and disk speed dependent |
| Find duplicates | Linear | Proportional to total file size |
| Tree view (10 levels) | ~200ms | Depends on directory breadth |
Recommended Settings
# Server configuration for optimal performance
MAX_CONCURRENT_OPERATIONS=10
REQUEST_TIMEOUT_SECONDS=300
BATCH_OPERATION_SIZE=1000
LOG_LEVEL=INFO # Use INFO in production, not DEBUG
πΊοΈ Roadmap
Phase 1: Core Foundation β
- [x] Basic CRUD operations
- [x] Directory management
- [x] File search and discovery
- [x] Archive operations
- [x] Utility tools (hash, cleanup)
- [x] Health checks and metadata
Phase 2: Advanced Features (Current)
- [x] Batch operations with rollback
- [x] Duplicate file detection
- [x] Directory comparison
- [x] Detailed logging and monitoring
Phase 3: Enterprise Features (Planned)
- [ ] File watch/monitoring service
- [ ] Encryption support (AES-256)
- [ ] Database integration for metadata
- [ ] Advanced permission models
- [ ] Distributed operations support
Phase 4: Integration & Expansion (Planned)
- [ ] Cloud storage backends (S3, GCS, Azure)
- [ ] Database file operations
- [ ] Media file processing
- [ ] Advanced analytics dashboard
π Future Enhancements
Planned Improvements
1. File Monitoring & Watching
# Future: Watch files for changes
await client.call_tool("watch_directory_tool", {
"path": "/home/user/documents",
"callback_url": "https://your-api.com/file-changes",
"filter": "*.pdf"
})
2. Encryption Support
# Future: Encrypt/decrypt files
await client.call_tool("encrypt_file_tool", {
"path": "/home/user/sensitive.txt",
"algorithm": "aes-256",
"password": "secure-password"
})
3. Cloud Storage Backends
# Future: Seamless cloud integration
await client.call_tool("upload_to_s3_tool", {
"local_path": "/home/user/backup.zip",
"s3_path": "s3://my-bucket/backups/",
"region": "us-west-2"
})
4. Media Processing
# Future: Image/video operations
await client.call_tool("create_thumbnail_tool", {
"image_path": "/home/user/photo.jpg",
"output_path": "/home/user/thumb.jpg",
"size": "256x256"
})
5. Sync Operations
# Future: Two-way sync between directories
await client.call_tool("sync_directories_tool", {
"source": "/home/user/local",
"destination": "/mnt/nas/backup",
"bidirectional": True,
"ignore_patterns": ["*.tmp", "node_modules"]
})
π€ Contributing
We welcome contributions from the community! Whether it's bug reports, feature requests, or code improvements, your help makes File Manager MCP better.
Getting Started
-
Fork the repository
git clone https://github.com/your-username/file-manager-mcp.git -
Create a feature branch
git checkout -b feature/your-feature-name -
Make your changes
- Follow PEP 8 style guidelines
- Write descriptive commit messages
- Add tests for new functionality
- Update documentation as needed
-
Commit and push
git commit -am "Add your feature description" git push origin feature/your-feature-name -
Open a Pull Request
- Describe your changes in detail
- Reference related issues
- Ensure all tests pass
Development Guidelines
- Code Style: Follow PEP 8 and use
blackfor formatting - Testing: Write unit tests for new features
- Documentation: Update docstrings and README
- Error Handling: Provide meaningful error messages
- Logging: Add appropriate log statements for debugging
Report Issues
Found a bug? Please open an issue with:
- Detailed description of the problem
- Steps to reproduce
- Expected vs actual behavior
- Environment details (Python version, OS, etc.)
- Relevant logs or error messages
Feature Requests
Have an idea for improvement? Create an issue with:
- Clear description of the feature
- Use cases and benefits
- Suggested implementation approach
- Any relevant examples
π License
File Manager MCP is licensed under the MIT License.
See the LICENSE file for full details.
Summary
The MIT License permits you to:
- β Use, modify, and distribute this software
- β Use it for commercial and private purposes
- β Include it in proprietary applications
With the conditions:
- π Include a copy of the license and copyright notice
- π State significant changes made to the software
π€ Author
Parth Rana
- GitHub: github.com/parthRana26
- Repository: github.com/parthRana26/file-manager-mcp
- Email: [contact via GitHub]
About
Parth Rana is a software engineer passionate about building robust, scalable systems for AI applications. File Manager MCP represents the intersection of practical filesystem management and modern AI agent architectures.
π Support & Community
- GitHub Issues: Report bugs or request features
- GitHub Discussions: Ask questions and discuss ideas
- MCP Documentation: modelcontextprotocol.io
- FastMCP Guide: FastMCP Documentation
π Learning Resources
Getting Started with MCP
Python & Async Programming
File System Best Practices
π Project Statistics
| Metric | Value |
|---|---|
| Total Tools | 34 |
| Lines of Code | ~3,000+ |
| Service Modules | 6 |
| Python Version | 3.11+ |
| License | MIT |
| Status | Production Ready |
| Last Updated | 2024 |
β Show Your Support
If you find File Manager MCP useful, please:
- β Star this repository
- π Share it with your network
- π¬ Provide feedback and suggestions
- π€ Contribute to the project
- π Write about it in your blog
Made with β€οΈ by Parth Rana
Last Updated: 2024 | Version: 1.0.0 | Status: Production Ready
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Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.