Caesar MCP Server

Caesar

Caesar is the search engine for AI, organising the world's data with a free API for web search and full-document reads.

Caesar is the search engine for AI, organising the world's data. Use the free API to search the web, read sources in full, and cite the sources used. No account required: the anonymous tier is live.

Start with an agent

For agents that support skills, install Caesar search directly:

npx skills add caesar-data/skills --skill caesar-search

<Prompt description="Use Caesar to search, read the most relevant result, cite the source URL, and preserve doc_id and search_id." actions={["copy"]}> {Use Caesar to search for "postgres 17 logical replication failover". Read the most relevant result, cite the source URL, and preserve doc_id and search_id.}

For agents: use `/llms.txt` to discover docs, append `.md` to any page for markdown, and start with `/agents/install` for client-specific setup.

Call the API directly

This works as written with only curl:

curl -s https://alpha.api.trycaesar.com/v1/search \
  -H "Content-Type: application/json" \
  -d '{"query": "postgres 17 logical replication failover", "max_results": 3}'

Each result includes a doc_id you can pass to /v1/document to read the page in full. Run the first search and read.

Search, read, cite

Get ranked documents from the web. Read the selected `doc_id` as markdown. Cite the returned source URL and capture metadata.

Search and read everywhere

Verb	Endpoint	What it does
search	POST /v1/search	Ranked retrieval over canonical documents and passages
read	POST /v1/document	Inspect one document and retrieve its content (full-page markdown with content.selection: "full_document")

The same search and read operations appear on every surface: search/read in the CLI and SDKs, web_search/web_fetch over MCP. Feedback is available from REST, the CLI, and SDKs when you need it.

Citable sources

Search results can drift: URLs change, snippets age, and the source an agent saw may not match what a human opens later. Caesar returns source metadata agents can keep with their answer:

• doc_id — deterministic identifier for a canonical document that can be reused across searches and recrawls. Read it in full any time with /v1/document.
• passage_id — identifier for a specific passage in the latest capture, with section context.
• search_id — identifier for the search itself, used to attribute feedback to the exact ranking that produced a result.
• capture_id and capture_time — exactly which capture of the document your content came from (on search results with response.verbosity: "full"; always available from /v1/document).

That means an agent can search, read the selected source, and cite where and when the content was captured. See provenance for the full object model.

Pick a surface

Three endpoints, an OpenAPI spec, and an interactive playground. Start here for raw HTTP. Canonical documents, passages, freshness, ranking, and source metadata. Free to use. Anonymous access works without a key; partner API keys add higher throughput. `pip install caesar-search` — sync and async clients, typed models, automatic retries. `npm install caesar-search` — fully typed, ESM and CJS, works in Node, Bun, Deno, and edge runtimes. `web_search` and `web_fetch` from the `caesar-search/ai` subpath. `caesar-search` — search and read from the shell, with a `--json` contract built for scripts and agents. Remote MCP endpoint at `/mcp` — generic web-search tools, no local install, one command to connect. Recipes for framework tools, generic tool calling, and Agent Development Kit projects. Install the search skill with `npx skills add`, or use the API installer for the full bundle.

Next steps

• Quickstart — search and read with nothing but curl.
• How search works - how Caesar turns public pages into citable documents and passages.
• Pricing - free access, anonymous tier, and partner keyed throughput.
• Authentication — what an API key changes, and why you may not need one yet.
• Agents guide — conventions for building agents on Caesar.