# Pickrate

> Pickrate measures whether AI agents pick your tool over competitors. We run real developer tasks across Claude, GPT, and Gemini and report your Pick Rate — the share of the time an agent actually chooses you.

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## Core
- [Leaderboards](https://pickrate.io/leaderboard.md): Pick Rate rankings across Claude, GPT, Gemini
- [Check a tool](https://pickrate.io/report?via=llms): look up any tool's Pick Rate
- [Methodology](https://pickrate.io/methodology.md): exactly how Pick Rate is measured
- [Features](https://pickrate.io/features.md)
- [Pricing](https://pickrate.io/pricing.md)
- [Trust & Security](https://pickrate.io/trust.md)

## Category leaderboards
- [AI SDK](https://pickrate.io/leaderboard/ai-sdk.md)
- [Product Analytics](https://pickrate.io/leaderboard/analytics.md)
- [API Gateway](https://pickrate.io/leaderboard/api-gateway.md)
- [Authentication](https://pickrate.io/leaderboard/auth.md)
- [Automation & Integrations](https://pickrate.io/leaderboard/automation.md)
- [Caching & KV](https://pickrate.io/leaderboard/caching.md)
- [CDN](https://pickrate.io/leaderboard/cdn.md)
- [CI/CD](https://pickrate.io/leaderboard/ci-cd.md)
- [Database & ORM](https://pickrate.io/leaderboard/database.md)
- [Documentation Platforms](https://pickrate.io/leaderboard/docs-platforms.md)
- [Feature Flags](https://pickrate.io/leaderboard/feature-flags.md)
- [Hosting & Deploy](https://pickrate.io/leaderboard/hosting.md)
- [Incident Management](https://pickrate.io/leaderboard/incident-mgmt.md)
- [Object Storage](https://pickrate.io/leaderboard/object-storage.md)
- [Error Monitoring](https://pickrate.io/leaderboard/observability.md)
- [Payments](https://pickrate.io/leaderboard/payments.md)
- [Background Jobs & Queues](https://pickrate.io/leaderboard/queues.md)
- [Search](https://pickrate.io/leaderboard/search.md)
- [SMS & Communications](https://pickrate.io/leaderboard/sms.md)
- [Transactional Email](https://pickrate.io/leaderboard/transactional-email.md)
- [Vector Database](https://pickrate.io/leaderboard/vector-db.md)
- [Work Management](https://pickrate.io/leaderboard/work-management.md)

## Programmatic access
Pickrate is callable by agents three ways, all returning the same data:
- MCP server (Streamable HTTP): `https://pickrate.io/api/mcp` — tools: getPickRate, getLeaderboard, lookupTool
- WebMCP (in-browser): [manifest](https://pickrate.io/.well-known/webmcp) — same tools via navigator.modelContext
- REST API: [OpenAPI spec](https://pickrate.io/openapi.json) · `GET https://pickrate.io/api/public/report?q=<tool>` · `GET https://pickrate.io/api/public/leaderboard?category=<slug>`

## Developer docs
- [Docs home](https://pickrate.io/docs.md): build with Pickrate
- [Agent Attribution](https://pickrate.io/docs/attribution.md): install attribution (touch/identify/convert), SDK `@pickrate/attribution`, signed webhooks, export API
- [Pick Rate API reference](https://pickrate.io/docs/api.md): public read API, authenticated eval API, MCP server

## Blog
- [Your SaaS Has a Billboard. The Agent Can’t Read It.](https://pickrate.io/blog/your-saas-has-a-billboard-the-agent-cant-read-it.md): Our first SaaS leaderboard — work management — finds the household names nearly invisible to AI agents. Linear leads, Jira is named-but-not-picked, and the tools with the biggest marketing barely register. As SaaS goes headless, the selection criteria flip.
- [An Agent Sent You a Customer. Your Analytics Called It “Direct.”](https://pickrate.io/blog/agent-attribution-your-analytics-calls-it-direct.md): AI agents are quietly driving signups your analytics files under “direct.” Why agent attribution is structurally hard, which parts are actually measurable, and why anyone promising perfect AI attribution is overselling.
- [We Measure Whether Agents Pick Tools. Now They Can Pick Pickrate.](https://pickrate.io/blog/pickrate-is-webmcp-native.md): Pickrate is now WebMCP-native: open it in Chrome and an in-browser AI agent can call its tools directly. Why being callable, not just recommended, is the next stage of Agent SEO.
- [Your Coding Agent Can Now Ask Pickrate Which Tool to Pick](https://pickrate.io/blog/pickrate-mcp-server.md): Pickrate is now a remote MCP server. Add one line to Cursor or Claude Desktop and your agent can query any tool's Pick Rate, mid-task. Why being callable is the whole point.
- [What Is Pick Rate? Measuring Whether AI Agents Choose Your Tool](https://pickrate.io/blog/what-is-pick-rate.md): Pick Rate is the share of the time an AI agent picks your tool over competitors on a real task. Here's what it measures, why citations aren't the same thing, and how to read it.
- [Mintlify Is Hot With Humans. AI Agents Barely Pick It.](https://pickrate.io/blog/mintlify-hot-with-humans-agents-dont-pick-it.md): We measured which documentation platforms AI agents recommend. The buzzy hosted names lose to old open-source frameworks — a textbook case of the corpus-presence gap.
- [Agent SEO: How to Get Recommended by AI Coding Agents](https://pickrate.io/blog/agent-seo-get-recommended-by-ai-coding-agents.md): Agent SEO is the discipline of getting AI coding agents to pick your tool. A practical checklist across the four stages agents move through before they choose you.
- [Why AI Agents Aren't Picking Your SDK (and How to Fix It)](https://pickrate.io/blog/why-ai-agents-arent-picking-your-sdk.md): If agents know your SDK exists but never import it, the problem is usually Discovery, not awareness. The Probe/Serve gap, llms.txt, OpenAPI, MCP, and unbranded prompts.
- [GEO vs. Agent Selection: Citations Aren't the Same as Getting Picked](https://pickrate.io/blog/geo-vs-agent-selection-citations-arent-getting-picked.md): GEO and brand-radar tools measure whether AI talks about you. Agent selection measures whether AI chooses you. Why the distinction decides what you optimize.
- [The Agent Funnel: The Four Observable Stages of Being Chosen by AI](https://pickrate.io/blog/the-agent-funnel-four-stages-of-being-chosen.md): Awareness, Discovery, Recommendation, Adoption. The four stages an AI agent moves through before it picks your tool — and how to find the one that's capping you.

## Awareness signal — corpus footprint
Each tool report shows its presence in the open pretraining corpus: Common Crawl (the raw web) and FineWeb (the filtered derivative models train on). A tool well-represented in Common Crawl but thin in FineWeb has an awareness gap at the source — crawled, but underweight in what models actually learned from. Strongest confirmed footprints (present in the FineWeb 10BT sample):
- [Bitbucket Pipelines](https://pickrate.io/leaderboard/ci-cd/bitbucket-pipelines.md): 31 in the FineWeb 10BT sample, 1,981 Common Crawl URLs
- [Netlify](https://pickrate.io/leaderboard/hosting/netlify.md): 31 in the FineWeb 10BT sample, 816 Common Crawl URLs
- [Elasticsearch](https://pickrate.io/leaderboard/search/elasticsearch.md): 25 in the FineWeb 10BT sample, 1,968 Common Crawl URLs
- [Cloudflare](https://pickrate.io/leaderboard/cdn/cloudflare.md): 18 in the FineWeb 10BT sample, 1,899 Common Crawl URLs
- [Twilio](https://pickrate.io/leaderboard/sms/twilio.md): 17 in the FineWeb 10BT sample, 1,965 Common Crawl URLs
- [GitLab CI/CD](https://pickrate.io/leaderboard/ci-cd/gitlab-ci.md): 14 in the FineWeb 10BT sample, 1,600 Common Crawl URLs
- [New Relic](https://pickrate.io/leaderboard/observability/newrelic.md): 12 in the FineWeb 10BT sample, 1,942 Common Crawl URLs
- [Auth0](https://pickrate.io/leaderboard/auth/auth0.md): 9 in the FineWeb 10BT sample, 1,811 Common Crawl URLs