Choose tools your AI agents can actually use.
Use these resources to compare APIs, CLIs, MCP servers, SaaS products, and internal platforms before autonomous agents depend on them.
Start with the decision you need to make
The useful question is not “does this tool have an API?” It is whether an agent can discover the right action, call it with bounded authority, verify the result, and recover safely when something goes wrong.
Choose a search API for agent workflows
Compare SerpAPI, Brave Search API, and Tavily for official-documentation retrieval using the May 2026 AgentFirstTools benchmark.
Build an official-docs retrieval loop
Help agents find, cite, and verify official documentation before they act on code, API, or infrastructure tasks.
Score any tool in 10–20 minutes
Rate inspectability, scriptability, bounded action, verification, recovery, and composability. Includes downloadable Markdown and CSV worksheets plus an inquiry path for high-stakes decisions.
Evaluate the interface layer
Use focused API, CLI, and MCP server checklists when you know which tool surface your agents will call.
Require action receipts
Replace vague success messages with durable IDs, status URLs, diffs, audit events, and next actions agents can cite and re-check.
Compare categories with evidence
Follow benchmark work for comparable agent-tool categories, starting with search APIs for agent tasks.
What usually breaks agent workflows
Hidden state
The agent cannot query permissions, current state, required fields, or recent changes before acting.
Ambiguous success
The tool returns a toast, spinner, or vague {"ok": true} response with no durable receipt.
Broad credentials
The only available token can mutate too much, so safe delegation depends on hope rather than scope.
Unsafe retries
Timeouts and partial failures can duplicate side effects because there is no idempotency or recovery path.