The full upstream README, mirrored here for reference. Install config, tool schemas, adoption signals, and an original overview live on the Agent Seo Engine listing page.
mcp-name: io.github.davidmosiah/agent-seo-engine
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🧱 Part of the Delx agent stack — 15 open-source MCP servers across body, reach and coordination.
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.
manifest, connection_status and privacy_audit surfaces before content toolsWith MCP support:
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.
All commands return structured JSON by default. Use --format markdown for human review.
Hermes-style config:
Recommended first calls:
agent_seo_connection_statusagent_seo_privacy_auditagent_seo_score_content| 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 |
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.