io.github.davidmosiah/agent-seo-engine

⭐ If this agent-first tool helps your workflow, please star the repo. Stars make this tooling easier for other builders to discover and help Delx keep shipping open infrastructure.
🧱 Part of the Delx agent stack — 15 open-source MCP servers across body, reach and coordination.

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Agent-first SEO scoring, search-intent detection and opportunity prioritization. It packages the useful parts of a production content pipeline into a clean local CLI plus an optional MCP server for Codex, Claude, Cursor, Hermes, OpenClaw and other agent runtimes.

Use it when an agent needs deterministic SEO checks before rewriting, refreshing or publishing content.

What It Does

• Classifies search intent: informational, navigational, transactional and commercial investigation
• Scores markdown articles for agent-readable SEO gaps
• Prioritizes GSC-style opportunities by impressions, position, CTR gap, conversions and commercial value
• Exposes manifest, connection_status and privacy_audit surfaces before content tools
• Runs locally by default with no required API keys

Install

pipx install agent-seo-engine

With MCP support:

pipx install "agent-seo-engine[mcp]"

Published on PyPI: agent-seo-engine. Release automation uses PyPI Trusted Publishing, so GitHub Actions can publish future versions without long-lived PyPI tokens. See docs/pypi-publishing.md.

CLI

agent-seo-engine manifest --client codex
agent-seo-engine doctor
agent-seo-engine privacy-audit
agent-seo-engine intent "best ai agent framework"
agent-seo-engine score --file examples/article.md --primary-keyword "ai agent testing"
agent-seo-engine opportunity --impressions 4200 --clicks 80 --position 12.4 --commercial-intent 0.8
agent-seo-engine image-alt --file page.html

All commands return structured JSON by default. Use --format markdown for human review.

MCP

agent-seo-mcp

Hermes-style config:

mcp_servers:
  agent_seo:
    command: agent-seo-mcp
    args: []
    sampling:
      enabled: false

Recommended first calls:

1. agent_seo_connection_status
2. agent_seo_privacy_audit
3. agent_seo_score_content

Agent Surfaces

Tool	Purpose
agent_seo_manifest	Install/runtime guidance for agent clients
agent_seo_connection_status	Local/offline readiness and optional integration status
agent_seo_privacy_audit	Draft, analytics and credential boundaries
agent_seo_detect_intent	Search intent classification
agent_seo_score_content	Markdown quality checks with exact recommendations
agent_seo_prioritize_opportunity	GSC-style opportunity scoring
agent_seo_check_image_alt	Image alt-attribute coverage audit for HTML

Copy-Paste Agent Prompt

Use agent-seo-engine. First call agent_seo_connection_status and agent_seo_privacy_audit.
Score the draft, then propose only edits tied to failed checks or high-impact opportunities.

Agent Contract

Agents should not guess whether a draft is ready. They should call the scoring tool, read exact failed checks, then propose focused edits. The engine is intentionally deterministic and local so repeated agent runs can compare output over time.

Development

python3 -m venv .venv
. .venv/bin/activate
pip install -e ".[dev]"
pytest
python -m compileall -q src

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📧 Contact & Support

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• 🐛 Bug reports / feature requests — GitHub Issues
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