chore: import upstream snapshot with attribution
This commit is contained in:
wehub-resource-sync
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---
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title: CodeRabbit
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sidebarTitle: CodeRabbit
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description: AI-powered code review tool
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---
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[CodeRabbit](https://coderabbit.ai) is an AI-powered code review tool that automatically reviews pull requests. By connecting Context7 as an MCP server, CodeRabbit can access up-to-date library documentation during reviews, helping it verify implementations against the latest API references and best practices.
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## Setup
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<Steps>
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<Step title="Navigate to MCP Servers">
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Go to your [CodeRabbit dashboard](https://app.coderabbit.ai) and navigate to **Integrations** → **MCP Servers**.
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</Step>
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<Step title="Add Context7">
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Click the **Add** button next to **Context7** MCP server.
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Add the following header for higher rate limits:
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| Header | Value |
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|--------|-------|
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| `CONTEXT7_API_KEY` | Your API key from the [Context7 dashboard](https://context7.com/dashboard) |
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```json
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{
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"CONTEXT7_API_KEY": "YOUR_API_KEY"
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}
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```
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</Step>
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<Step title="Connect">
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Click the **Connect** button to connect the server.
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</Step>
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<Step title="Enable for Public Repos">
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To use Context7 with public repositories, go to **Organization Settings** → **Configuration** → **Knowledge Base**. In the MCP section, select **Enabled** instead of **Auto** and click **Apply Changes**.
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</Step>
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</Steps>
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## Usage Guidance
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In the **Usage Guidance** field, you can instruct CodeRabbit on how to use Context7 during reviews. For example:
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```
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Use Context7 to look up documentation for any libraries used in the code being reviewed.
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Verify that API usage matches the latest documentation and flag any deprecated patterns.
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```
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## How It Works
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Once connected, CodeRabbit will query Context7 for relevant library documentation when reviewing pull requests. This helps CodeRabbit:
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- Verify correct API usage against the latest documentation
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- Identify deprecated methods or patterns
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- Suggest improvements based on library best practices
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- Provide more accurate and informed review comments
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---
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title: Factory AI
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sidebarTitle: Factory AI
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description: AI-native software development platform with Droids
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---
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[Factory AI](https://factory.ai) is a coding agent platform that uses "Droids" to handle development tasks. By connecting Context7 as an MCP server, Factory Droids can access up-to-date library documentation during coding tasks.
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For more details on how Factory AI handles MCP, see the [Factory AI MCP documentation](https://docs.factory.ai/cli/configuration/mcp).
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## Setup
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There are multiple ways to add Context7 as an MCP server in Factory AI. Replace `YOUR_API_KEY` with your API key from the [Context7 dashboard](https://context7.com/dashboard).
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### Using the CLI
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```bash
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droid mcp add context7 https://mcp.context7.com/mcp --type http --header "CONTEXT7_API_KEY: YOUR_API_KEY"
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```
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### Using the MCP Manager
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Run the `/mcp` command inside Factory and add Context7 from the interface.
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### Using a Configuration File
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Add Context7 directly to your `.factory/mcp.json` (project-level) or `~/.factory/mcp.json` (user-level):
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```json
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{
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"mcpServers": {
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"context7": {
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"type": "http",
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"url": "https://mcp.context7.com/mcp",
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"headers": {
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"CONTEXT7_API_KEY": "YOUR_API_KEY"
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}
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}
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}
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}
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```
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## How It Works
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Once connected, Factory Droids will query Context7 for relevant library documentation during coding tasks. This helps Droids:
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- Use correct API signatures and patterns from the latest documentation
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- Avoid deprecated methods or outdated usage patterns
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- Generate implementations aligned with library best practices
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- Produce higher-quality code with fewer revision cycles
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@@ -0,0 +1,81 @@
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---
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title: GitHub Actions
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sidebarTitle: GitHub Actions
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description: Automatically refresh your Context7 library when your docs change
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---
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Keep your Context7 documentation in sync by triggering a refresh whenever you push to your main branch.
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## Setup
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<Steps>
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<Step title="Get your API key">
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Go to your [Context7 dashboard](https://context7.com/dashboard) and copy your API key.
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</Step>
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<Step title="Add the API key as a repository secret">
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In your GitHub repository, go to **Settings** → **Secrets and variables** → **Actions** and add a new secret:
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| Name | Value |
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|------|-------|
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| `CONTEXT7_API_KEY` | Your API key from the Context7 dashboard |
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</Step>
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<Step title="Create the workflow file">
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Add the following file to your repository at `.github/workflows/context7-refresh.yml`:
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```yaml
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name: Refresh Context7 Docs
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on:
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push:
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branches:
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- master # change to your default branch if different
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jobs:
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refresh:
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runs-on: ubuntu-latest
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steps:
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- name: Trigger Context7 Refresh
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run: |
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curl -s -X POST https://context7.com/api/v1/refresh \
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-H "Content-Type: application/json" \
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-H "Authorization: Bearer ${{ secrets.CONTEXT7_API_KEY }}" \
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-d '{"libraryName": "/${{ github.repository }}"}'
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```
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This uses `${{ github.repository }}` to automatically resolve to your repository's `owner/repo` (e.g., `vercel/next.js`). If your library ID on Context7 differs from your GitHub repository name, replace it with the correct value (e.g., `/your-org/your-repo`).
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</Step>
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</Steps>
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## Refreshing a Specific Branch
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To refresh a non-default branch, add the `branch` field to the request body. The `branch` value must match a branch name that already exists on your library in Context7.
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```yaml
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- name: Trigger Context7 Refresh
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run: |
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curl -s -X POST https://context7.com/api/v1/refresh \
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-H "Content-Type: application/json" \
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-H "Authorization: Bearer ${{ secrets.CONTEXT7_API_KEY }}" \
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-d '{"libraryName": "/your-org/your-repo", "branch": "v2"}'
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```
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<Note>
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If the branch has not been added to your library on Context7, the refresh will fail with a `branch_not_found` error.
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</Note>
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## Private Repositories
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For private repositories, include a `gitToken` so Context7 can access your code:
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```yaml
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- name: Trigger Context7 Refresh
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run: |
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curl -s -X POST https://context7.com/api/v1/refresh \
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-H "Content-Type: application/json" \
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-H "Authorization: Bearer ${{ secrets.CONTEXT7_API_KEY }}" \
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-d '{"libraryName": "/your-org/your-repo", "gitToken": "${{ secrets.GIT_ACCESS_TOKEN }}"}'
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```
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<Note>
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Private sources require a Pro or Enterprise plan. See the [Private Sources](/howto/private-sources) guide for more details.
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</Note>
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@@ -0,0 +1,68 @@
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---
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title: Mastra
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sidebarTitle: Mastra
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description: TypeScript framework for building AI agents
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---
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[Mastra](https://mastra.ai) is a TypeScript framework for building AI agents. It provides first-class MCP support through its `MCPClient` class. By connecting Context7 as an MCP server, your Mastra agents can access up-to-date library documentation, enabling them to generate accurate code and answer technical questions with current API references.
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For more details on how Mastra handles MCP, see the [Mastra MCP documentation](https://mastra.ai/docs/mcp/overview).
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## Setup
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<Steps>
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<Step title="Install the MCP Package">
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Add the Mastra MCP package to your project:
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```bash
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npm install @mastra/mcp@latest
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```
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</Step>
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<Step title="Create an MCP Client">
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Configure an `MCPClient` that connects to Context7:
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```typescript
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import { MCPClient } from "@mastra/mcp";
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const context7 = new MCPClient({
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id: "context7",
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servers: {
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context7: {
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url: new URL("https://mcp.context7.com/mcp"),
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requestInit: {
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headers: {
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CONTEXT7_API_KEY: process.env.CONTEXT7_API_KEY!,
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},
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},
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},
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},
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});
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```
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Set `CONTEXT7_API_KEY` in your environment with your API key from the [Context7 dashboard](https://context7.com/dashboard).
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</Step>
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<Step title="Connect to Your Agent">
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Pass the Context7 tools to your Mastra agent:
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```typescript
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import { Agent } from "@mastra/core/agent";
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const agent = new Agent({
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id: "coding-assistant",
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name: "Coding Assistant",
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instructions: "You are a helpful coding assistant with access to up-to-date library documentation via Context7.",
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model: "anthropic/claude-sonnet-4-6",
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tools: await context7.listTools(),
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});
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```
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</Step>
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</Steps>
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## How It Works
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Once connected, your Mastra agents will query Context7 for relevant library documentation. This helps agents:
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- Answer technical questions with accurate, up-to-date API references
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- Generate code that follows current library patterns and best practices
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- Avoid hallucinating outdated or incorrect API usage
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- Provide version-specific guidance for any supported library
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@@ -0,0 +1,36 @@
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---
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title: Tembo
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sidebarTitle: Tembo
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description: Orchestration layer for AI-powered engineering workflows
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---
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[Tembo](https://tembo.io) is a platform for orchestrating AI coding agents across repositories and integrations. Context7 is available as a built-in MCP integration in Tembo, giving agents access to up-to-date library documentation.
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For more details on how Tembo handles MCP, see the [Tembo MCP documentation](https://docs.tembo.io/integrations/mcp).
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||||
## Setup
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||||
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<Steps>
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<Step title="Navigate to Integrations">
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Go to the **Integrations** page in your Tembo dashboard. You'll see Context7 listed under **MCP Servers**.
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</Step>
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<Step title="Install Context7">
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Click the **Install** button on the **Context7** card.
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</Step>
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<Step title="Verify Connection">
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After installation, Context7 will appear under your **Installed** integrations.
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||||
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</Step>
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</Steps>
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||||
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||||
## How It Works
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||||
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||||
Once connected, Tembo agents will query Context7 for relevant library documentation during tasks. This helps agents:
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- Generate correct implementations based on the latest API references
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- Identify deprecated patterns during automated code reviews
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- Produce PRs that follow current library best practices
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- Reduce back-and-forth by getting it right the first time
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Reference in New Issue
Block a user