Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add agents/evalstate/fast-agent/runninggit clone --depth 1 https://github.com/evalstate/fast-agentWhat 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 | $0.00000 | $0.00867 |
| Opus 5 | $0.00000 | $0.00434 |
| Sonnet 5 | $0.00000 | $0.00173 |
| Haiku 4.5 | $0.00000 | $0.00087 |
Grade C, and why
running scanned grade C with 1 finding 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 2d 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.
Hidden instructionshighPrompt injection
Directives inside HTML comments, invisible characters or bidirectional overrides are read by the model and not by the person reviewing the file.
<!-- ### Connecting to MCP Servers Connect to MCP servers from other FastAgent applications by configuring them in your `fast-agent.yaml`: ```yaml mcp: servers: my_remote_agent: transport: "sse" url: "http://localhost:80 How it starts
The opening of the file, as written. The whole thing — 157 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deploy and Run
fast-agent provides flexible deployment options to meet a variety of use cases, from interactive development to production server deployments.
Interactive Mode
Run fast-agent programs interactively for development, debugging, or direct user interaction.
import asyncio
from fast_agent.core.fastagent import FastAgent
fast = FastAgent("My Interactive Agent")
@fast.agent(instruction="You are a helpful assistant")
async def main():
async with fast.run() as agent:
# Start interactive prompt
await agent()
if __name__ == "__main__":
asyncio.run(main())
When started with uv run agent.py, this begins an interactive prompt where you can chat directly with the configured agents, apply prompts, save history and so on.
Command Line Execution
fast-agent supports command-line arguments to run agents and workflows with specific messages.
# Send a message to a specific agent
uv run agent.py --agent default --message "Analyze this dataset"
# Override the default model
uv run agent.py --model gpt-4o --agent default --message "Complex question"
# Run with minimal output
uv run agent.py --quiet --agent default --message "Background task"
This is perfect for scripting, automation, or one-off queries.
The --quiet flag switches off the Progress, Chat and Tool displays.
MCP Server Deployment
Any fast-agent application can be deployed as an MCP server with a simple command-line switch.
Starting an MCP Server
# Start as a Streamable HTTP server (http://localhost:8080/mcp)
uv run agent.py --transport http --port 8080
# Start as a stdio server
uv run agent.py --transport stdio
Each configured agent is exposed as an MCP tool for sending messages to that agent.
The MCP Server can also be started programmatically.
Programmatic Server Startup
import asyncio
from fast_agent.core.fastagent import FastAgent
fast = FastAgent("Server Agent")
@fast.agent(instruction="You are an API agent")
async def main():
# Start as a server programmatically
await fast.start_server(
transport="http",
port=8080,
server_name="API-Agent-Server",
server_description="Provides API access to my agent",
tool_description="Send a message to the {agent} agent",
)
if __name__ == "__main__":
asyncio.run(main())
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.
- 2d ago First seen · 157 lines · 0 tokens per session scan C fcf1a2540ce6
running is an agent published in the GitHub repository evalstate/fast-agent (3,904 stars, last pushed 2d ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 867 tokens. A static security scan graded it C with 1 finding (hidden instructions). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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