"GPT-SoVITS MCP (Model Context Protocol) Integration" matching MCP connectors:
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Signed, traced record of what an npm package or file attempts when run, network included. No key.
HefestoAI checks AI-generated code before you ship it.
Recover project context, review recorded decisions, and steer queued work across AI coding agents.
**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 MCP that shrinks coding-agent context before the model call; architecture checks without an LLM. Zero data retention.
MCP server for secureFlows: token-free URL builders and integration-linting tools for AI agents.
Agentic code review, no signup to try: reality gates + frontier-model review, with veto.
MCP server providing Pine Script v6 documentation. Enables AI to: Look up Pine Script functions and validate syntax Access official documentation for indicators, strategies, and visuals Understand Pine Script concepts (execution model, repainting, etc.) Generate correct v6 code with proper function references
Scan pasted Stripe webhook/checkout code for common integration bugs.
Repository knowledge graph MCP server for codebase understanding and debugging.
Multi-model code review: a panel of models + detectors return a pass/fail verdict. Paid via x402.
Project memory, semantic code search, and grounded agent context.
## 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
Project memory for coding agents: requirements, decisions, code graph and delivery telemetry.
Behavioral drift context (Behavioral Load Map, hot paths, release brief) for coding agents, per PR.
Deterministic context layer for your codebase: change impact, blast radius, answers with receipts.
A paid remote MCP for code graph MCP for AI coding, built to return verdicts, receipts, usage logs,