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Use this page when an AI agent should read documents, choose the right Pulse tools, and return grounded output with minimal custom code.

Fast Path

1

Create an API key

Open the Pulse Platform, create an API key, and keep it out of source control.
2

Connect an MCP client

Use the hosted server for URL-based documents. Use the local server when the agent must read files from disk.
3

Give the agent a document

Hosted MCP needs a public or pre-signed file_url. Local MCP can use either file_url or an absolute file_path.
4

Run extract first

Most workflows start with extract. Use the returned extraction_id for schema, split, and table tools.
5

Poll when needed

If any tool returns { "status": "processing", "job_id": "..." }, call get_job until the job completes.

Client Configs

~/.codex/config.toml
See Connecting a client for Claude Desktop, VS Code, and more setup options.

First Agent Prompt

Give the agent the document location, the output you want, and any evidence requirements:
For long or mixed documents, be explicit about the plan:

Tool Paths

Extraction Settings Agents Should Know

Agents can pass the same high-impact extraction settings you use in the Platform: For the broader Platform/API view of these settings, see Processing Parameters.

Agent Guardrails

  • Hosted MCP cannot read local disk paths. Use a public or pre-signed URL.
  • Local MCP can read an absolute file_path, but chat attachments are not automatically file paths.
  • Always reuse extraction_id instead of re-extracting the same document.
  • Poll get_job before passing a result into the next tool.
  • Ask for a schema before writing JSON to a database or downstream system.
  • Keep API keys out of prompts, logs, screenshots, and committed config.
  • For regulated workflows, return page references, footnote links, chunks, or bounding boxes whenever users need evidence.

MCP Tools

Full tool parameters and return shapes.

Sample Documents

Public documents agents can use for smoke tests.