Odel
Send Email

Send Email

@hal9aiPythonUpdated 5 days ago

Send emails from natural language prompts.

View on GitHub
Server endpointStreamable HTTPOAuthProbed

This is the third-party server itself — Odel doesn't run it. Hitting this URL directly talks straight to the upstream server with no auth or proxying. Connect through Odel to front it with managed auth.

mcp.build

mcp.build is a community to build open source MCPs (Model Context Protocol servers) that adopted the Hal9 open source agent structure for its ease of use for deployment and interoperability.

Website: hal9ai.github.io/mcp.build (GitHub Pages from /docs)

This repo is structured so coding agents (Claude Code, Grok Build, Cursor, Codex, …) can contribute with minimal guesswork. Start at AGENTS.md and docs/llms.txt.

Why Hal9 agents?

Hal9 agents are intentionally simple: read from stdin with input(), write to stdout with print(). No framework lock-in. That shape maps cleanly to how MCPs expose tools to models, and makes agents easy to:

  • Develop — plain Python, any library
  • Deployhal9 deploy or GitHub Actions to hal9.com
  • Interoperate — same agent can run as a chatbot, an API, or an MCP tool

Agents

AgentDescriptionPath
send-emailSend emails with Resend from natural language prompts (Groq tool use)send-email/

send-email

Example prompt:

send email to javier@hal9.ai with text hello!

The agent:

  1. Reads the prompt via input()
  2. Calls a Groq model with a send_email tool definition
  3. Maps the tool call to the Resend API
  4. Prints the result via print()

Environment variables

VariableRequiredDescription
GROQ_API_KEYYesAPI key from console.groq.com
RESEND_API_KEYYesAPI key from resend.com
RESEND_FROMNoSender address (default: mcp.build <onboarding@resend.dev>)
GROQ_MODELNoModel id (default: qwen/qwen3.6-27b)

Local run

cd send-email
pip install -r requirements.txt
export GROQ_API_KEY=...
export RESEND_API_KEY=...
echo "send email to you@example.com with text hello!" | python app.py

Deploy to Hal9

export HAL9_TOKEN=...   # from https://hal9.com/devs
hal9 deploy send-email --name send-email --access public \
  --title "Send Email" \
  --description "Send emails via Resend using natural language prompts"

On push to main, if files under send-email/ change, .github/workflows/send-email.yaml deploys a new version to Hal9 (same pattern as hal9ai/hal9 app deploy workflows). Set the HAL9_TOKEN repository secret in GitHub Actions.

Publish to the MCP Registry

The hosted send-email MCP is published as a remote-only server to the official MCP Registry under io.github.hal9ai/send-email. Metadata lives in send-email/server.json. On push to main (when send-email/ changes), .github/workflows/publish-send-email.yaml publishes it using GitHub OIDC — no extra GitHub secrets. The registry version is version in that file. If it is already published, the job skips. Bump version there to ship a new registry entry.

Website (GitHub Pages)

Static site lives in docs/ — no build step.

PathRole
docs/index.htmlLanding page — what mcp.build is + list of available MCPs
docs/send-email/index.htmlDedicated page per MCP (usage, "Add to Claude", etc.) — template for new MCPs
docs/css/styles.cssStyles
docs/agents.jsonMachine-readable agent catalog
docs/llms.txtShort instructions for LLMs / agents
AGENTS.mdFull rules for coding agents

Enable Pages: repo Settings → Pages → Build and deployment → Source: Deploy from a branch → Branch: main → Folder: /docs.

Contributing an agent (MCP)

This repo is designed so coding agents (Claude Code, Grok Build, Cursor, Codex, …) and humans can contribute a new MCP with minimal guesswork. Full checklist: AGENTS.md. Use send-email/ as the reference implementation and .github/workflows/send-email.yaml as the deploy pattern.

Expected layout

# minimum
my-tool/
  app.py               # input() → work → print()
  requirements.txt     # optional
  hal9.yaml            # optional welcome

# also update
.github/workflows/my-tool.yaml
docs/agents.json
docs/my-tool/index.html   # dedicated docs page for the MCP
README.md

Minimal agent

# my-tool/app.py
prompt = input()
# … call APIs, tools, models …
print(result)

Steps

  1. Create a new folder at the repo root, e.g. my-tool/. Keep the name short, kebab-case.

  2. Add app.py. Use input() / print() (or any stdin/stdout) so the agent stays Hal9- and MCP-friendly. Prefer no hal9 package unless you need session state.

  3. Add a requirements.txt if you need third-party packages.

  4. Optionally add hal9.yaml with a welcome: message.

  5. Add a GitHub Actions workflow, .github/workflows/my-tool.yaml, that deploys when that folder changes:

    on:
      push:
        branches: [main]
        paths:
          - my-tool/**
          - .github/workflows/my-tool.yaml
    # job: pip install hal9 → checkout → if my-tool/ changed:
    hal9 deploy my-tool --name my-tool --access public \
      --title "My Tool" --description "…"
    

    Secret: HAL9_TOKEN (agent runtime keys like GROQ_API_KEY are configured on the Hal9 side / local env — never committed).

  6. Register the agent in docs/agents.json (include an id, description, and docs_path pointing at its docs page) and mention it in the table above.

  7. Add a dedicated docs page at docs/<my-tool>/index.html so it shows up at https://hal9ai.github.io/mcp.build/my-tool/ (or https://mcp.build/my-tool/). Copy docs/send-email/index.html as a template — it covers what the MCP does, how agents use it, and how to add it to Claude and other MCP clients.

  8. Do not commit secrets; document required env vars in this README.

License

Contributions are welcome. Individual agents may carry their own licenses; see each folder for details.