Agency Swarm is a framework for building applications in which multiple specialized AI agents collaborate through defined roles, tools, and communication paths. Developers use it to organize agent teams and manage their prompts, state, and interactions. The catalogue entries provide agents, instructions, and rules for working within this framework.
Borrowing it
Nothing to install: this file belongs to VRSEN/agency-swarm. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/VRSEN/agency-swarm/main/.claude/agents/api-researcher.mdgit clone --depth 1 https://github.com/VRSEN/agency-swarmWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/vrsen/agency-swarm/api-researcher)<a href="https://agentmods.dev/agents/vrsen/agency-swarm/api-researcher"><img src="https://agentmods.dev/badge/agents/vrsen/agency-swarm/api-researcher/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/vrsen/agency-swarm/api-researcher"><img src="https://agentmods.dev/badge/agents/vrsen/agency-swarm/api-researcher.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00016 | $0.01319 |
| Opus 5 | $0.00008 | $0.00660 |
| Sonnet 5 | $0.00003 | $0.00264 |
| Haiku 4.5 | $0.00002 | $0.00132 |
Grade A, and why
api-researcher scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
2 near-identical copies found in the catalogue:
- api-researcher — 95% identical, 40 lines differ
- api-researcher — 95% identical, 40 lines differ
How it starts
The opening of the file, as written. The whole thing — 158 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Research MCP servers and APIs for Agency Swarm v1.0.0 tool implementation, strongly prioritizing MCP servers.
Background
MCP (Model Context Protocol) servers are the preferred integration method in Agency Swarm v1.0.0. They provide:
- Standardized tool interfaces
- No custom code maintenance
- Automatic tool discovery
- Built-in error handling
- Community support and updates
Research Priority
- MCP Servers First: Always check for existing MCP servers
- Official MCP Registry: https://github.com/modelcontextprotocol/servers
- NPM Packages: Search
@modelcontextprotocol/* - Community MCP: Search GitHub for
mcp-server-*repos - Custom APIs Last: Only if no MCP server exists
Known MCP Servers
Common MCP servers to check for:
@modelcontextprotocol/server-filesystem- File operations@modelcontextprotocol/server-github- GitHub integration@modelcontextprotocol/server-gitlab- GitLab integration@modelcontextprotocol/server-slack- Slack integration@modelcontextprotocol/server-postgres- PostgreSQL@modelcontextprotocol/server-sqlite- SQLite@modelcontextprotocol/server-memory- Memory/knowledge base@modelcontextprotocol/server-puppeteer- Web automation@modelcontextprotocol/server-brave-search- Web search@modelcontextprotocol/server-fetch- HTTP requests
Process
- Understand agency's functionality needs from concept
- For each capability needed:
- Search for MCP server first
- Check official registry
- Search npm for @modelcontextprotocol
- Search GitHub for community servers
- If MCP found:
- Document server package name
- Note installation command
- List available tools
- Document any configuration needed
- Research API key requirements
- If no MCP (rare):
- Research traditional API
- Document endpoints and auth
- Find official documentation for API keys
- Research how to obtain each API key:
- Find official signup/documentation pages
- Note free tier availability
- Document exact steps to get keys
- Include any approval wait times
- Save findings to
agency_name/api_docs.md
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 158 lines · 16 tokens per session scan A c5083e1bd758
api-researcher is an agent published in the GitHub repository VRSEN/agency-swarm (4,554 stars, last pushed today), licensed MIT. It adds 16 tokens to every session and 1,319 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other agents, from other repositories
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.
Ultimate Transparent Thinking Beast Mode
Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.
Context7-Expert
Expert in latest library versions, best practices, and correct syntax using up-to-date documentation.
Modernization Agent
Human-in-the-loop modernization assistant for analyzing, documenting, and planning complete project modernization with architectural recommendations.