mcpcentral-io/langchain-prompts-mcp-server
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The LangChain Prompts MCP Server provides seamless access to the LangSmith prompt library, offering a vast collection of community-vetted AI prompts.
LangChain Prompts MCP Server
Overview
A Model Context Protocol (MCP) server that provides seamless access to the LangSmith prompt library—the world's largest collection of community-vetted AI prompts. With over 1000+ battle-tested prompts, advanced search capabilities, and rich metadata including usage statistics and version history, this server transforms how you discover and integrate prompts into your AI workflows. Access professional-grade prompts through natural language queries, making prompt engineering instantly actionable across Claude Desktop, Claude Code, and other MCP-compatible clients.
Background
Our MCP Server connects directly to LangSmith, LangChain's official platform for prompt management and LLM application development. The server provides intelligent access to a vast ecosystem of prompts that have been created, tested, and refined by the AI community.
Core Capabilities:
- Prompt Discovery: Search and filter through thousands of public prompts by name, owner, description, or tags
- Rich Metadata: Access download counts, view statistics, likes, and community engagement metrics
- Version Control: Track prompt evolution with full version history and commit information
- Template Intelligence: Work with parameterized prompts including input/output schemas
- Advanced Analytics: Get library-wide statistics, trending prompts, and popularity metrics
LLM-Enhanced Features:
- Intelligent Completions: Context-aware prompt completion suggestions
- Prompt Validation: Automated quality checks and best practice validation
- Similarity Search: Find related prompts based on content and structure
- Comparative Analysis: Side-by-side prompt comparison with detailed insights
Authentication & Access:
- Public Library: Access thousands of community prompts without authentication
- Private Prompts: Authenticate with LangSmith API key for private prompt access
- User Collections: Browse prompts by specific creators and organizations
MCP Client Configuration
Known Client Compatibility:
- Claude Desktop
- Claude Code
- OpenAI ChatGPT (via Custom Connectors)
- Cursor IDE
- Continue.dev
- VS Code (with MCP extension)
Claude Desktop
{
"mcpServers": {
"langchain-prompts": {
"command": "npx",
"args": ["-y", "mcp-remote", "https://mcp.prompts.mcpcentral.io/mcp"],
"env": {
"LANGSMITH_API_KEY": "your-api-key-optional"
}
}
}
}
Claude Code
claude mcp add langchain-prompts -s user --transport http https://mcp.prompts.mcpcentral.io/mcp
OpenAI ChatGPT (Custom Connectors)
Use the MCP endpoint URL: https://mcp.prompts.mcpcentral.io/mcp
Cursor IDE & Continue.dev
{
"mcpServers": [
{
"name": "langchain-prompts",
"url": "https://mcp.prompts.mcpcentral.io/mcp",
"env": {
"LANGSMITH_API_KEY": "your-api-key-optional"
}
}
]
}
MCP Version Compatibility
MCP 2025-06-18 Compliance
- Protocol Version: 2025-06-18 with full specification compliance
- Structured Output: Enhanced tools with comprehensive schemas
- Resource Support: Dynamic collections with real-time updates
- Prompt Templates: Guided workflows for prompt discovery and analysis
- Title Fields: All tools, resources, and prompts include descriptive titles
- Transports: stdio + Streamable HTTP with custom Workers transport
Enhanced Compatibility
- OpenAI Integration: Compatible with ChatGPT Custom Connectors
- Enterprise Ready: Built-in rate limiting and security controls
- Cloud Optimized: Deployed on Cloudflare Workers for global availability
Prompt Management Tools (13 Total)
- List Prompts: Browse public prompts with filtering and pagination
- Search Prompts: Advanced search with multiple filter criteria
- Get Prompt: Retrieve detailed prompt information including metadata
- Get Prompt Statistics: Access library-wide analytics and trends
- Like/Unlike Prompt: Engage with community prompts (requires auth)
- Get Prompt Versions: Track prompt evolution and changes
- Get User Prompts: Browse prompts by specific creators
- Get Popular Prompts: Discover trending and high-engagement prompts
- Get Prompt Content: Access actual prompt templates and schemas
- Compare Prompts: Analyze multiple prompts side-by-side
- Validate Prompt: Check prompt quality and best practices
- Get Prompt Completions: Intelligent auto-completion suggestions
Dynamic Resources (3 Total)
- Popular Prompts Collection: Real-time trending prompts
- Recent Prompts Collection: Latest community contributions
- Trending Prompts Collection: Engagement-based recommendations
Guided Prompts (4 Total)
- Analyze Prompt: Comprehensive prompt effectiveness analysis
- Discover Prompts: Guided exploration of the prompt library
- Find Similar Prompts: Discover related prompts by similarity
- Improve Prompt: Get suggestions for prompt enhancement
Available Tools
| Tool | Name | Description | Parameters |
|---|---|---|---|
| List Prompts | list_prompts | List public prompts from LangSmith with optional filtering | limit, owner, search |
| Get Prompt | get_prompt | Get detailed information about a specific prompt | prompt_name |
| Get Prompt Statistics | get_prompt_statistics | Get statistics about the prompt library | None |
| Search Prompts | search_prompts | Advanced search for prompts with comprehensive filtering | query, owner, tags, is_public, min_likes, min_downloads, sort_by, sort_order, limit |
| Like Prompt | like_prompt | Like a specific prompt (requires authentication) | prompt_name |
| Unlike Prompt | unlike_prompt | Remove like from a specific prompt (requires authentication) | prompt_name |
| Get Prompt Versions | get_prompt_versions | Get version history and commits for a specific prompt | prompt_name, limit |
| Get User Prompts | get_user_prompts | Get prompts created by a specific user | username, include_private, limit |
| Get Popular Prompts | get_popular_prompts | Get trending and popular prompts | time_period, category, limit |
| Get Prompt Content | get_prompt_content | Get the actual prompt template content and configuration | prompt_name, version, include_model_config |
| Compare Prompts | compare_prompts | Compare multiple prompts side by side | prompt_names, comparison_criteria |
| Validate Prompt | validate_prompt | Validate prompt structure and quality | prompt_name, check_completeness, check_best_practices |
| Get Prompt Completions | get_prompt_completions | Get intelligent auto-completions for prompt templates | partial_text, context, max_suggestions |
Available Resources
| Resource | URI | Description |
|---|---|---|
| Popular Prompts Collection | langsmith://collections/popular | Collection of trending and popular prompts |
| Recent Prompts Collection | langsmith://collections/recent | Recently updated prompts |
| Trending Prompts Collection | langsmith://collections/trending | Prompts trending by engagement |
Available Prompts
| Prompt | Name | Description | Arguments |
|---|---|---|---|
| Analyze Prompt | analyze-prompt | Analyze prompt effectiveness, structure, and areas for improvement | prompt_content (required), analysis_depth (optional), target_audience (optional) |
| Discover Prompts | discover-prompts | Discover prompts based on use case, domain, or specific requirements | use_case (optional), domain (optional), requirements (optional) |
| Find Similar Prompts | find-similar-prompts | Find prompts similar to a given example or description | reference_prompt (optional), similarity_criteria (optional), limit (optional) |
| Improve Prompt | improve-prompt | Get suggestions to improve an existing prompt | prompt_content (required), improvement_goals (optional), target_model (optional) |
Architecture
Key Technical Features
- Dual Transport Design: stdio for local development, HTTP for production
- Custom Workers Transport: Optimized for Cloudflare Workers (54% smaller than standard)
- Type Safety: Full TypeScript implementation with runtime validation
- Intelligent Caching: Multi-tier caching for optimal performance
- Rate Limiting: Built-in protection with configurable limits
- Security First: Input validation, injection protection, and secure error handling
Performance Optimizations
- Bundle Size: 507KB optimized bundle for serverless deployment
- Cold Start: Minimal latency with Worker-optimized initialization
- Cache Strategy: LRU caching with TTL for frequently accessed prompts
- Retry Logic: Exponential backoff with jitter for resilient API calls
Data Overview
Primary Data Source: LangSmith Prompt Hub
- Content: 1000+ community-vetted prompts from smith.langchain.com
- Metadata: Download counts, view statistics, likes, tags, and version history
- Templates: Parameterized prompts with input/output schemas
- Updates: Real-time access to latest community contributions
- Privacy: Public prompts accessible without auth, private with API key
Version Information
- Version: 1.0.0
- Protocol: MCP 2025-06-18
- SDK: @modelcontextprotocol/sdk 1.16.0
- Features: Full specification compliance with resources, prompts, and structured output
- Transports:
- stdio: Default MCP transport for direct client integration
- http: MCP 2025-06-18 Streamable HTTP with header validation
Testing
- MCP Central Lab: Test the server interactively at https://lab.mcpcentral.io/
MCP Registry
This server is published in the official Model Context Protocol Registry. The registry configuration enables:
- Server Discovery: Automatic detection by MCP-compatible clients
- Remote Access: HTTP transport endpoint at
https://mcp.prompts.mcpcentral.io/mcp - Package Distribution: Available via npx for instant access
- Client Compatibility: Verified support for Claude Desktop, Claude Code, and more
- Feature Declaration: 13 tools, 3 resources, 4 prompts with advanced search capabilities
Support
- Documentation: MCP Documentation
- LangSmith: LangSmith Platform
- Health Check:
GET https://mcp.prompts.mcpcentral.io/healthfor status monitoring
Working Examples
Example 1: Prompt Discovery for Developers
Scenario: A developer wants to find the best prompts for code review and documentation.
Tools Used: search_prompts, get_prompt_content, compare_prompts
- Search for Code Review Prompts: Use search_prompts with query "code review"
- Get Template Details: Retrieve full content for top results
- Compare Options: Use compare_prompts to analyze differences
Expected Results: Curated code review prompts with templates, best practices, and community ratings.
Example 2: Building a Prompt Library for Your Team
Scenario: A team lead wants to standardize prompts across their organization.
Tools Used: get_popular_prompts, validate_prompt, get_prompt_versions
- Discover Popular Prompts: Get trending prompts in your domain
- Validate Quality: Check prompts against best practices
- Track Changes: Monitor version history for selected prompts
Expected Results: Validated, high-quality prompts with version control for team standardization.
Example 3: AI Assistant Enhancement
Scenario: An AI engineer wants to improve their assistant's response quality.
Tools Used: analyze-prompt, find-similar-prompts, improve-prompt
- Analyze Current Prompts: Use the analyze-prompt workflow
- Find Better Alternatives: Discover similar high-performing prompts
- Get Improvement Suggestions: Use improve-prompt for optimization
Expected Results: Enhanced prompts with measurable improvements in response quality and consistency.
Example 4: Research and Experimentation
Scenario: A researcher needs to understand prompt engineering patterns across different use cases.
Tools Used: get_prompt_statistics, list_prompts, get_user_prompts
- Analyze Library Statistics: Understand overall trends and patterns
- Browse by Category: Explore prompts across different domains
- Study Expert Contributions: Examine prompts from top creators
Expected Results: Comprehensive understanding of prompt patterns, trends, and best practices in the community.