MCP server

Web Search API Eval

io.github.psinglap/websearch-api-eval

Checked 28 Oct 2026, 09:03 UTC · Connected to it and listed its tools

Web search API benchmark for AI agents: You.com, Tavily, Exa, Parallel. Results and charts.

Website Source

At a glance

Type

MCP server

Publisher

Not verified

Status

Working at last check

Tools

11

Token cost

About 1,413 tokens per request

Sets up in

Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok

Last checked

28 Oct 2026, 09:03 UTC

Connect it to your agent

Add to CursorAdd to VS CodeVS Code Insiders

Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.

Claude Code

claude mcp add --transport http websearch-api-eval https://websearch-api-eval.psberkeleymba.workers.dev/mcp

Claude Desktop

Settings → Connectors → Add custom connector, and paste the URL.

Codex (config.toml)

[mcp_servers.websearch-api-eval]
url = "https://websearch-api-eval.psberkeleymba.workers.dev/mcp"

Gemini CLI

{"mcpServers":{"websearch-api-eval":{"httpUrl":"https://websearch-api-eval.psberkeleymba.workers.dev/mcp"}}}

Cursor

{"mcpServers":{"websearch-api-eval":{"url":"https://websearch-api-eval.psberkeleymba.workers.dev/mcp"}}}

VS Code

{"servers":{"websearch-api-eval":{"type":"http","url":"https://websearch-api-eval.psberkeleymba.workers.dev/mcp"}}}

Antigravity

agy mcp add websearch-api-eval https://websearch-api-eval.psberkeleymba.workers.dev/mcp

ChatGPT

Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.

OpenAI API (Responses tools)

{"type":"mcp","server_label":"websearch-api-eval","server_url":"https://websearch-api-eval.psberkeleymba.workers.dev/mcp","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"websearch-api-eval","server_url":"https://websearch-api-eval.psberkeleymba.workers.dev/mcp"}

Tools

• compare_providers ~232 tokens
  Compare two or more of You.com, Tavily, Exa and Parallel side by side, overall or within one use case, optionally filtered to metrics whose name contains a keyword (e.g. 'latency', 'accuracy', 'fresh', 'cost', 'empty').
• fetch ~94 tokens
  Full text of one benchmark document by its ID (for example question-F5, scorecard-finance, overall, methodology).
• get_charts ~178 tokens
  The published graphs: overall scorecard, key metrics and per-query grids for GTM, insurance and finance, and developer activation. Without chart_id, lists them with titles and image links; with chart_id, also returns the image.
• get_methodology ~85 tokens
  How the benchmark was run and graded: query design, identical request parameters, 3 runs per query, latency timing, SimpleQA and FreshQA grading, the 10 metrics and the standards they follow, and limits.
• get_overall_results ~113 tokens
  Headline findings and the overall scorecard across all 30 queries (90 calls per API): accuracy, fully correct, precision@5, freshness, empty responses, failed calls, latency p50/p95, cost per correct answer. Also the per-use-case summary, which API fits which agent, and developer activation time.
• get_question ~117 tokens
  One benchmark question by ID (e.g. G3, I4, F5): the task, search call, parameters, answer key with sources, and what each API returned with its accuracy score (0-2, mean of 3 runs).
• get_scorecard ~158 tokens
  Full metric scorecard for one use case (gtm, insurance, finance) or 'overall'. Metrics: search-only latency p50/p95 (server and client), calls under 1 s, accuracy, freshness (% in window, newest relevant result age), content in one call, tokens, search cost.
• how_to_run_locally ~65 tokens
  How to rerun this benchmark on your own machine with your own API keys, including on your own queries. Nothing runs on this server.
• list_questions ~118 tokens
  The 30 benchmark questions (G1-G10 GTM, I1-I10 insurance, F1-F10 finance): ID, what the agent is asked, the search call and freshness.
• recommend_provider ~151 tokens
  Which web search API fits an agent, based on this benchmark: live voice/chat turns, deep research, semantic or long-tail queries, docs lookups, or a specific use case (GTM, insurance, finance). Returns the guidance with the supporting numbers.
• search ~102 tokens
  Search the Web Search API Eval benchmark (results, questions, methodology, charts, how to run). Returns matching document IDs, titles and URLs.

Browse

• GitHub tools
• Exa tools
• Web search
• GitHub and code hosting

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