> For the complete documentation index, see [llms.txt](https://syv-labs.gitbook.io/context-pool/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://syv-labs.gitbook.io/context-pool/ide-setup/cursor.md).

# Cursor

## Setup

The easiest way is to run the install script:

```bash
curl -fsSL https://raw.githubusercontent.com/syv-labs/cxp/main/install.sh | sh
```

Or, if you already have the binary:

```bash
cxp install
```

This writes the `contextpool` MCP entry to `~/.cursor/mcp.json` and runs the backend setup wizard. Your API key is saved to the system keychain — no need to hardcode it in the config file.

Restart Cursor to activate.

***

## LLM Backend

`cxp install` runs a wizard that lets you choose and save your backend. Run it interactively:

```bash
cxp install --setup
```

```
Which backend should ContextPool use for summarization?

  1) Claude Code  — free, uses your Claude Code subscription
                    (slower, ~1 subprocess at a time)
  2) Anthropic API — direct API, billed per token, fastest
                    (parallelizes well, works headless)
  3) OpenAI API
  4) NVIDIA NIM
  5) Skip — I'll configure this later
```

Your choice is saved to the system keychain. The MCP subprocess picks it up automatically — no env vars in the config file needed.

***

## Manual API Key (Alternative)

If you prefer to manage keys explicitly — or if you're on a machine where the keychain isn't available — you can pass the key directly in `~/.cursor/mcp.json`:

```json
{
  "mcpServers": {
    "contextpool": {
      "command": "cxp",
      "args": ["mcp"],
      "env": {
        "ANTHROPIC_API_KEY": "sk-ant-..."
      }
    }
  }
}
```

Supported env vars: `ANTHROPIC_API_KEY`, `OPENAI_API_KEY`, `NVIDIA_API_KEY`. If an env var is set, it takes precedence over the keychain.

***

## Use Agent Mode

ContextPool works in **Agent mode** in Cursor. The agent calls `fetch_project_context` automatically before responding. In regular chat mode (non-agent), the tools aren't invoked automatically — you'd need to ask explicitly.

***

## Pre-populate Memory

```bash
cd your-project/
cxp init cursor --local
```

Processes all Cursor sessions for this project and writes summaries to `./ContextPool/`. Sessions with no extractable insights are skipped — no empty files. Run once after setup; the MCP tool handles incremental indexing from there.

***

## Troubleshooting

**Tools not appearing in Cursor** Restart Cursor after running `cxp install`. Check **Settings → MCP** to confirm the server status shows green.

**"No LLM backend available"** Run `cxp install --setup` to configure a backend. If you set a key via the wizard, verify it was saved: run `cxp install --setup` again — it will show the existing key and ask if you want to reuse it.

**Sessions not found** Cursor stores transcripts in `~/.cursor/`. If you're using a non-standard Cursor installation, pass `--cursor-dir` to `cxp init cursor` with the correct path.


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://syv-labs.gitbook.io/context-pool/ide-setup/cursor.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.