ecourts-mcp-server

ecourts-mcp-server

Connects LLMs to the EcourtsIndia Partner API for searching Indian court cases, retrieving orders, reading cause lists, and accessing AI summaries.

Category
访问服务器

README

ecourts-mcp-server v1.2.0

An MCP (Model Context Protocol) server that connects LLMs to the EcourtsIndia Partner API v1.3, enabling AI agents to search Indian court cases, retrieve orders, read cause lists, and access AI-generated summaries.

Tools (9 total)

Tool Description Billing
ecourts_get_case Full case detail by CNR — parties, orders, IAs, notices, documents, hearings, FIR, linked cases, file AI status, case AI analysis Per-request
ecourts_lookup_case Workflow tool — find a case by human-readable number (e.g. "CS(OS) 123/2024") instead of CNR, returns full details Per-request
ecourts_search_cases Rich search with 30+ filter params, year filters, date ranges, faceted aggregations Per-request
ecourts_get_order Download order PDF with metadata (certified true copies) Per-request
ecourts_get_order_ai Extracted order text + pre-computed AI analysis (summary, outcome, key points) Per-request
ecourts_get_court_structure Browse state → district → complex → court hierarchy Free
ecourts_search_causelist Search cause list entries across all courts ₹1/request
ecourts_get_causelist_dates Available cause list dates Free
ecourts_refresh_case Queue a fresh scrape of case data Per-request

Quick Start

npm install
npm run build
export ECOURTS_API_TOKEN="eci_live_your_token_here"
npm start

Deployment

Docker

# Build
docker build -t ecourts-mcp-server .

# Run
docker run -d \
  -e ECOURTS_API_TOKEN=eci_live_your_token_here \
  -p 3000:3000 \
  ecourts-mcp-server

# Health check
curl http://localhost:3000/health

Docker Compose

# Set your token
export ECOURTS_API_TOKEN=eci_live_your_token_here

# Start
docker compose up -d

# Verify
curl http://localhost:3000/health

Cloud Deployment

The Docker image works with any container platform:

  • AWS ECS / Fargate — Use the health check endpoint at /health
  • Google Cloud Run — Set PORT=8080 (Cloud Run default), server auto-adapts
  • Azure Container Apps — Standard HTTP container deployment
  • Railway / Render / Fly.io — Push the Dockerfile, set ECOURTS_API_TOKEN in secrets

The image runs as a non-root user, includes a HEALTHCHECK, and defaults to HTTP transport on port 3000.

Claude Desktop (stdio)

{
  "mcpServers": {
    "ecourts": {
      "command": "node",
      "args": ["/path/to/ecourts-mcp-server/dist/index.js"],
      "env": {
        "ECOURTS_API_TOKEN": "eci_live_your_token_here"
      }
    }
  }
}

Claude Code (stdio)

claude mcp add ecourts -- node /path/to/ecourts-mcp-server/dist/index.js

Running Tests

npm test                # 110 unit tests via vitest
npm run test:integration  # 24 integration tests (requires ECOURTS_API_TOKEN)
npm run test:all          # both

Tests cover: query parameter serialization, all formatting functions, facet rendering, all 14 API error code branches, schema boundary validation, safeHandler wrapper, truncation, date validation, and typed fields. Integration tests cover court structure hierarchy, case search with filters/sort/years, case detail, order metadata, cause list search by date, case refresh, and error scenarios.

CI/CD

The .github/workflows/ci.yml pipeline:

  1. Build & test on Node 20 and 22 (on push/PR to main)
  2. Docker build + health check on push to main

Architecture

src/
├── index.ts              # Entry point, transport (stdio/HTTP), health endpoint
├── constants.ts          # Base URLs, character limits
├── types.ts              # Full TypeScript interfaces for all API responses
├── schemas/index.ts      # Zod input validation with date regex enforcement
├── services/
│   ├── api-client.ts     # HTTP client, binary download, repeated-key array serializer, error handling
│   └── formatting.ts     # Markdown formatters for case, search, causelist, order
└── tools/index.ts        # 9 tool registrations with MCP annotations

Environment Variables

Variable Required Description
ECOURTS_API_TOKEN Yes EcourtsIndia Partner API bearer token
TRANSPORT No stdio (default) or http
PORT No HTTP port (default 3000, only for http transport)

Changelog

v1.2.0 (current)

Code Quality:

  • Eliminated all unsafe type casts — linkCases, subordinateCourt, and firDetails are now proper typed fields on CourtCaseData
  • CauseListEntry expanded with petitionerAdvocates, respondentAdvocates, internalCaseNo, dateCreated, dateModified
  • Proper AvailableDatesResponse and CaseFileSummary types replace inline anonymous types
  • All date parameters validated with YYYY-MM-DD regex at schema level

New Features:

  • ecourts_lookup_case — workflow tool that finds cases by human-readable number (e.g. "CS(OS) 123/2024") instead of CNR
  • Order file status in case detail — ecourts_get_case now shows which orders have AI analysis available with summary previews
  • Health check endpoint — GET /health for load balancers and container orchestrators
  • Error-safe HTTP transport — Express handler now catches errors instead of hanging
  • ecourts_get_order PDF download — returns order PDF as embedded resource with metadata (filename, file size) extracted from HTTP headers

Deployment:

  • Multi-stage Dockerfile (22MB Alpine image, non-root user, HEALTHCHECK)
  • docker-compose.yml with health check and token validation
  • GitHub Actions CI (Node 20/22 matrix, Docker build verification)
  • Test suite expanded to 110 unit tests + 24 integration tests

v1.1.0

  • Fixed array parameter serialization (courtCodes, caseTypes, etc.)
  • Added isError flag on MCP error responses
  • Complete error code handling (11 API error codes)
  • 15+ new search parameters (year filters, date ranges, categories, bench types)
  • Facet counts in search output
  • Comprehensive case detail formatting (all sections)

v1.0.0

  • Initial release with 8 tools covering all EcourtsIndia Partner API endpoints

推荐服务器

Baidu Map

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。

官方
精选
JavaScript
Playwright MCP Server

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。

官方
精选
TypeScript
Magic Component Platform (MCP)

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。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

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。

官方
精选
本地
TypeScript
VeyraX

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。

官方
精选
本地
graphlit-mcp-server

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。

官方
精选
TypeScript
Kagi MCP Server

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。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

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。

官方
精选