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Give your coding agent direct access to your production and development data. This is especially powerful when debugging - instead of switching between your editor and dashboard, your agent can pull the exact runs, errors, and user interactions it needs to understand what’s going wrong and fix it in place. MCP is powered by insight search, so your agent can query your production data with natural language and use that context to find root causes, fix issues, and optimize your agent.

Prerequisites

  • A Context Company account with at least one project sending data
  • An MCP-compatible IDE or tool (Cursor, Claude Code, Windsurf, or any client that supports MCP)

Setup

One-click install via OAuth — no API key needed. For CI, programmatic, or headless setups, see Advanced: API key.
1

Install and sign in

Add the server to Cursor using the Access Data page in your dashboard (use the Add to Cursor button), or paste the config below into Settings > MCP Servers:
After installing, click Connect next to context-company in Cursor to sign in via OAuth.
2

Try it out

Try this prompt:

Advanced: API key

For CI, programmatic, or headless setups where OAuth isn’t practical, you can authenticate with a read-only API key instead.
Cursor may ignore Authorization headers when the MCP server advertises OAuth discovery — we recommend the OAuth flow above for Cursor. API keys still work for Claude Code, CI, and other programmatic or headless MCP clients.
1

Generate an API key

Go to the Access Data page in your dashboard and create a read-only API key.Keys are prefixed with tcc_key and are read-only - they can only query your data, not ingest traces.
Copy your key immediately. You won’t be able to see it again.
When creating a key, choose an access scope:
2

Add to your IDE

Run this in your terminal:
Replace <your-api-key> with the key you generated.

Available tools

For most questions, insight_search is the right choice — it’s a multi-step analytics agent with full SQL access to your telemetry and synthesizes evidence across runs, sessions, patterns, failures, and costs. The other tools fetch raw traces and lists, and are best used when you already have a specific ID or want a filtered list of runs/sessions. Ask natural-language questions about your production data including metrics, patterns, failures, sessions, costs, and more. See insight search for details and example queries.
Insight search queries production data only and requires a Pro or Enterprise plan.

get_agent_runs

Fetch a filtered raw list of runs for dev or prod. A session/run matches when its run-level fields match the supplied filters. summary (the default) returns compact runs with prompt/response previews and failed step/tool-call summaries. full_trace includes all steps and tool calls using preview text only.

get_agent_sessions

Fetch a filtered list of sessions for dev or prod. A session matches when any run in that session matches the time, metadata, errored-only, and run-level failure text filters.

get_agent_run

Fetch the full raw trace of a single run by ID, including all steps and tool calls. Use this only when you need the complete step-by-step trace of a specific run.

get_agent_session

Fetch a specific production session by session ID.

Example prompts

Frustration debugging
Find the biggest reason users have been frustrated in my runs this past week. Look at my codebase to find the root cause and fix it.
Tool failure chains
Find runs where a tool call failed right after another tool succeeded. What’s the most common pattern, and what in my code is causing it?
Cost optimization
Find my most expensive runs from the past week. Figure out which prompts or tool loops are driving up cost and suggest code changes to reduce token usage.
Redundant tool loops
Find runs where my agent called the same tool more than 3 times in a row. Is there a loop in my code causing redundant calls? Fix it.
Task failure improvement
Show me runs with task failure patterns. Compare what the user asked for vs what the agent did, and suggest how to improve my system prompt.