Context7 - Coval Documentation

Context7 indexes library documentation and serves it to AI coding agents through an MCP server. Instead of relying on training data that may be outdated, your agent pulls live Coval docs on demand.

Why Use Context7

AI coding agents often hallucinate API details or reference outdated patterns. Context7 solves this by fetching current documentation at query time:

Always current — pulls from the latest published docs, not stale training data
Code-first — returns relevant code snippets and examples, not walls of text
Zero config — works out of the box with any MCP-compatible agent

Coval on Context7

Coval’s full documentation is indexed and available:

Coval on Context7

Browse the Coval library on Context7 — includes CLI commands, API examples, metric configuration, and more.

Install the Context7 MCP Server

Add Context7 to your agent’s MCP configuration:

Claude Code
Cursor
Windsurf

claude mcp add context7 -- npx -y @upstash/context7-mcp@latest

Add to .cursor/mcp.json:

{
  "mcpServers": {
    "context7": {
      "command": "npx",
      "args": ["-y", "@upstash/context7-mcp@latest"]
    }
  }
}

Add to your MCP config file:

{
  "mcpServers": {
    "context7": {
      "command": "npx",
      "args": ["-y", "@upstash/context7-mcp@latest"]
    }
  }
}

Usage

Once installed, your agent has two tools available:

1. Resolve Library ID

Find Coval’s library ID by searching for it:

resolve-library-id("Coval")
→ /llmstxt/coval_dev_llms_txt

2. Query Documentation

Ask questions and get back relevant code snippets and docs:

query-docs("/llmstxt/coval_dev_llms_txt", "how to create a metric with the CLI")

Your agent calls these tools automatically when it needs Coval context. You can also prompt it explicitly:

“Use Context7 to look up how Coval metrics work”

Example Workflow

Here’s what happens when your agent uses Context7 with Coval:

You ask a question

“How do I launch an evaluation run with the Coval CLI?”

Agent resolves the library

The agent calls resolve-library-id("Coval") and gets /llmstxt/coval_dev_llms_txt.

Agent queries the docs

It calls query-docs with your question and gets back current CLI examples and flags.

Agent responds with accurate info

You get a response grounded in the latest Coval documentation, not training data.

Context7 vs Other Approaches

Approach	Freshness	Setup	Best For
Context7 MCP	Live (latest docs)	One command	Quick lookups, any MCP agent
Agent Skills	Updated on install	`npx skills add`	Deep evaluation workflows
Coval MCP Server	Live (API calls)	`npx coval-mcp`	Executing operations directly
llms.txt	Live (latest docs)	Point agent at URL	Manual context loading

Context7 complements Skills and the Coval MCP server. Use Context7 when your agent needs to look something up. Use Skills when it needs to know how to evaluate well. Use the Coval MCP server when it needs to execute operations.

AI Agents

​Why Use Context7

​Coval on Context7

Coval on Context7

​Install the Context7 MCP Server

​Usage

​1. Resolve Library ID

​2. Query Documentation

​Example Workflow

​Context7 vs Other Approaches

Why Use Context7

Coval on Context7

Install the Context7 MCP Server

Usage

1. Resolve Library ID

2. Query Documentation

Example Workflow

Context7 vs Other Approaches