"Finding Information About Public Places" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
Free deterministic security scan of public git repos: OSV.dev vulnerable deps, secrets, config lint.
Find what to fix on a public website, for search engines and for AI answers.
Production-safety audits for AI-generated code, with a fix for every finding.
**Can AI actually read your page?** ChatGPT, Perplexity, Claude and Google's AI Overviews fetch pages very differently from your browser — no JavaScript, tight timeouts, and a robots.txt rulebook of their own. Lekta fetches a URL exactly the way they do and grades what survives, **A+ to F**. This is the technical half of **AEO** (answer engine optimization) and **GEO** (generative engine optimization): before a model can cite you, it has to be able to fetch you, parse you, and find one sentence worth quoting. **The loop this server was built for:** `Audit https://mysite.com/pricing with Lekta, apply the fixes it lists, audit it again, and show me the difference.` Your agent gets a graded verdict, a ranked fix plan with the exact markup to paste, and a diff that proves the change landed. Repeat until A+. **Four layers, 100 points:** **Access** 25 — do the ~17 AI crawler tokens get past robots.txt? **Indexability** 25 — how much content survives without JavaScript? **Answerability** 30 — is there a single quotable sentence an engine can lift? **Recency** 20 — can a model tell when this page was last true? **What this is not:** a rank tracker. Lekta will not tell you how often ChatGPT mentions your brand. It tells you whether your page can be read and quoted when it does — the part you can actually fix. **No black box.** Every finding cites its basis — an RFC, a vendor doc, or a dated measurement we ran. The engine is versioned with a public changelog: a score never moves without a published shift table. **Tools:** `lekta_audit` (fresh fetch) · `lekta_report` (cached read) · `lekta_fix_plan` (ranked, paste-ready) · `lekta_diff` (before/after) · `lekta_my_sites` Listing tools is open. Tool calls need a free key from lekta.dev/en/panel/api — send `Authorization: Bearer lekta_…` or `x-api-key`. Cached reads, fix plans and diffs cost nothing; only fresh fetches count against the daily limit. **Topics:** AEO · GEO · AI SEO · LLM SEO · answer engine optimization · generative engine optimization · AI crawler access (GPTBot, ClaudeBot, PerplexityBot, Google-Extended) · JavaScript-free indexability · structured data · content freshness
Hosted, no-auth endpoint of feldspar-scan: free deterministic security scan of a public git repository (OSV.dev vulnerable dependencies, secret patterns, config lint) as structured JSON. Tools: scan_repository(url), audit_pricing(). Stateless streamable-HTTP JSON-RPC, rate-limited. Source: https://github.com/project-feldspar-resources/feldspar-scan (MIT). Operated by Feldspar, an autonomous AI agent (Project Feldspar).
Scan a public GitHub repo, explain risks, get fix prompts and rescan to confirm fixes.
Read-only scan of a public GitHub repo for leaked secrets, with a 0-100 grade.
Architecture diagrams, explanations and Mermaid source for public GitHub repositories.
Scan any public GitHub MCP-server repo for security issues. 37 MCP-specific L1 rules, 8 languages.
Independent static verification for exact immutable public GitHub commits.
Audit and repair any public GitHub repo. Free survey; paid source, unified diffs and a pull request.
Code intelligence for LLMs. Analyze, search, and retrieve code from any public git repository.
OSS libs in your stack, really used: source, tests, callers. C#, Java, TS, Python, Rust, PHP+.
Read-only, source-backed compatibility lookups and approved changes for ResolveMesh's catalog.
An MCP server that gives your AI access to the source code and docs of all public github repos
Software Heritage MCP. The archive of public source code: which repositories have been archived…
Grade Claude Code, Gemini CLI and Cursor configs for risky permissions; get public config stats.
## Skill Catalog The library contains 42 public skills organized by Rails development concern. | Category | Examples | |----------|----------| | Planning | `create-prd`, `generate-tasks`, `plan-tickets` | | Testing | `plan-tests`, `write-tests`, `test-service`, `triage-bug` | | Code quality | `code-review`, `respond-to-review`, `security-check`, `refactor-code` | | Architecture and DDD | `define-domain-language`, `review-domain-boundaries`, `model-domain`, `review-architecture` | | Rails imple
Scan a public GitHub repo for known Vercel Python-runtime deploy footguns.
Bee governed intelligence for chat, code, research, documents, and memory.
Screens public GitHub repos and PRs to generate risk maps, findings, and merge-readiness signals.
Permission-aware onboarding MCP server: answers about a codebase, filtered by the caller's role.
Tell your assistant you're about to launch. It checks the app your builder synced to GitHub, tells you what would break for real users, hands you the fix, and re-checks after the sync. Point it at any public repo first (nothing to install, nothing to grant) and see exactly what comes back before you connect the one that matters.
Scan a GitHub repository for vulnerabilities, with proof for every finding, from your coding agent.
Compare two JSON files deeply without worrying about key or array order. Detect missing, extra, an…
