CIViC MCP Server
Enables structured queries and data analysis of cancer genomics information by interfacing with the Clinical Interpretation of Variants in Cancer (CIViC) API. It converts GraphQL responses into queryable SQLite tables for efficient clinical interpretation and natural language interaction.
README
CIViC MCP Server
This is a Cloudflare Workers-based Model Context Protocol (MCP) server that provides tools for querying the CIViC (Clinical Interpretation of Variants in Cancer) API. The server converts GraphQL responses into queryable SQLite tables using Durable Objects for efficient data processing.
The CIViC database is a crowd-sourced repository of clinical interpretations of cancer variants. This MCP server enables structured queries and data analysis of cancer genomics information through natural language interactions with AI assistants.
MCP Specification Compliance
This server implements MCP 2025-06-18 specification with the following compliance status:
✅ Implemented Features
- Structured Tool Output: Tools return structured JSON data with
_metafields - Protocol Version Headers: Supports
MCP-Protocol-Versionheader handling - Title Fields: Tools include human-friendly titles for display
- Meta Fields: Extensive use of
_metafields for additional context - Error Handling: Proper error responses with structured content
🔄 Partially Implemented
- Tool Annotations: Configuration ready but SDK integration pending
readOnlyHint,destructiveHint,idempotentHint,openWorldHintdefined- Need SDK update to support annotation parameters
⚠️ Pending Implementation
- Streamable HTTP Transport: Currently uses SSE transport
- Action Required: Migrate from HTTP+SSE to Streamable HTTP per MCP 2025-03-26
- Status: Architecture change needed for proper implementation
- OAuth 2.1 Authorization: Not implemented
- Action Required: Add OAuth 2.1 support for secure remote server access
- Components: Authorization Server discovery, Resource Indicators (RFC 8707)
- JSON-RPC Batching: Properly removed (was added in 2025-03-26, removed in 2025-06-18)
Tool Annotations Reference
The server defines comprehensive tool annotations for MCP clients:
// GraphQL Query Tool
annotations: {
readOnlyHint: false, // Creates/modifies data in SQLite
destructiveHint: false, // Non-destructive data staging
idempotentHint: false, // Different queries produce different results
openWorldHint: true // Interacts with external CIViC API
}
// SQL Query Tool
annotations: {
readOnlyHint: true, // Only reads data
destructiveHint: false, // Cannot modify data (read-only SQL)
idempotentHint: true, // Same query produces same results
openWorldHint: false // Operates on closed SQLite database
}
Future Updates Required
1. Transport Layer Migration
// Current: SSE Transport (deprecated)
CivicMCP.serveSSE("/sse").fetch(request, env, ctx)
// Target: Streamable HTTP Transport (MCP 2025-03-26+)
// Implementation requires MCP SDK architectural updates
2. Tool Annotation Integration
// Current: SDK doesn't support 5-argument tool() method
this.server.tool(name, description, schema, handler, annotations) // ❌
// Target: Find correct SDK pattern for annotations
// May require MCP SDK update or different approach
3. Authorization Framework
// Required: OAuth 2.1 integration with:
// - Authorization Server discovery (.well-known endpoints)
// - Resource Indicators (RFC 8707)
// - Dynamic client registration (RFC 7591)
// - PKCE-enabled authorization code flow
Specification Changelog Summary
MCP 2025-03-26 (Implemented)
- ✅ Tool annotations framework
- ⚠️ Streamable HTTP transport (pending)
- ✅ Audio data support (infrastructure ready)
- ⚠️ OAuth 2.1 authorization (pending)
MCP 2025-06-18 (Current Target)
- ✅ Structured tool output
- ✅ Enhanced
_metafields - ✅ Protocol version headers
- ✅ Title fields for tools
- ❌ JSON-RPC batching removed (properly removed)
- ⚠️ Enhanced authorization security (pending)
Features
- GraphQL to SQL Conversion: Automatically converts CIViC API responses into structured SQLite tables
- Efficient Data Storage: Uses Cloudflare Durable Objects with SQLite for data staging and querying
- Smart Response Handling: Optimizes performance by bypassing staging for small responses, errors, and schema introspection queries
- Two-Tool Pipeline:
civic_graphql_query: Executes GraphQL queries and stages large datasetscivic_query_sql: Enables SQL-based analysis of staged data
Installation & Configuration
Prerequisites
- A Cloudflare account
- Wrangler CLI installed
- Claude Desktop app
Deploy to Cloudflare Workers
-
Clone this repository:
git clone <repository-url> cd civic-mcp-server -
Install dependencies:
npm install -
Deploy to Cloudflare Workers:
npm run deploy -
After deployment, you'll get a URL like:
https://civic-mcp-server.YOUR_SUBDOMAIN.workers.dev
Configure Claude Desktop
Add this configuration to your claude_desktop_config.json file:
{
"mcpServers": {
"civic-mcp-server": {
"command": "npx",
"args": [
"mcp-remote",
"https://civic-mcp-server.quentincody.workers.dev/sse"
]
}
}
}
Replace quentincody with your actual Cloudflare Workers subdomain.
Usage
Once configured, restart Claude Desktop. The server provides two main tools:
civic_graphql_query: Execute GraphQL queries against the CIViC APIcivic_query_sql: Query staged data using SQL
Prompts
This server exposes three MCP Prompts that guide the model to use the civic_graphql_query tool with correct GraphQL syntax and robust search strategies:
Individual Data Type Prompts
get-variant-evidence— Generates GraphQL for Evidence Items only (no variantName filter - not supported by CIViC schema)get-variant-assertions— Generates GraphQL for Assertions only with systematic fallback strategies
Combined Data Prompt
get-variant-data— Executes both Evidence Items AND Assertions queries for comprehensive variant analysis
Examples (VS Code Copilot Chat / slash-commands):
/get-variant-evidence molecularProfileName:"TP53 Mutation" diseaseName:"Lung Adenocarcinoma" evidenceType:"PROGNOSTIC" first:"200"/get-variant-assertions molecularProfileName:"TPM3-NTRK1 Fusion" therapyName:"Larotrectinib" status:"ALL"/get-variant-data molecularProfileName:"BRAF V600E" diseaseName:"Melanoma" therapyName:"Trametinib" status:"ALL"
Key Prompt Features
- Bulletproof GraphQL Generation: Complete, validated queries that never fail
- Intelligent Search Strategies: Automatic fallback approaches to find relevant data
- Comprehensive Results: Evidence items include clinical descriptions; assertions provide high-level summaries
- Optimal Filtering: Default status is "ALL" to avoid over-filtering; null parameters are automatically excluded
- Proper URL Generation: Canonical links for verification (evidence:
/evidence/{id}, assertions:/assertions/{id})
These prompts provide complete GraphQL queries with proper CIViC v2 schema compliance and systematic search methodologies that ensure data discovery even when users provide imperfect parameters.
Example Queries
You can ask Claude questions like:
- "What are the latest evidence items for BRAF mutations?"
- "Show me all therapeutic interpretations for lung cancer variants"
- "Find genes with the most evidence items in the CIViC database"
Claude will use the server (and its civic_graphql_query tool) to fetch the relevant data from the CIViC database and present it to you. The server is designed to query version 2 of the CIViC API, ensuring you get up-to-date information.
If you encounter issues or Claude doesn't seem to be using the CIViC data, double-check the configuration steps above.
Response handling
The server intelligently optimizes context usage by storing large results in a temporary SQLite database. When GraphQL responses meet certain criteria, the raw response is returned directly instead of creating a database:
- Small responses (< 1500 characters): Returned directly to avoid unnecessary overhead
- Error responses: Passed through directly to make troubleshooting easier
- Empty/null responses: Bypassed to avoid creating empty databases
- Schema introspection queries: Queries containing
__schema,__type, or other introspection patterns are returned directly since they contain metadata rather than data suitable for SQL conversion
This optimization makes the server more efficient and provides better error visibility while still enabling powerful SQL-based analysis for substantial datasets.
Dataset management
Two helper endpoints are available outside of the SSE interface for managing staged datasets.
GET /datasets– lists the currently availabledata_access_ids with creation time and basic metadata.DELETE /datasets/:id– removes the specified dataset and frees storage.
Example:
curl https://civic-mcp-server.YOUR_SUBDOMAIN.workers.dev/datasets
curl -X DELETE https://civic-mcp-server.YOUR_SUBDOMAIN.workers.dev/datasets/abcd-1234
License
MIT License with Academic Citation Requirement - see LICENSE.md
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。