"IBM MCP Context Forge - Model Context Protocol Framework" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
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.
Audits any live MCP server URL or GitHub repo on Glama's 6-dimension TDQS rubric and compiles dro.
**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
Recover project context, review recorded decisions, and steer queued work across AI coding agents.
LLM cost optimization gateway, repo token-waste auditor & model arbitrage MCP server.
LLM cost optimization gateway, repo token-waste auditor & model arbitrage MCP server.
15 deterministic AI agent and developer tools for code context pruning, token budgeting, hybrid search reranking, self-healing patches, AST analysis, circular dependency detection, root-cause isolation, schema compilation, math/financial solving, critical-path scheduling, A/B testing, memory diffs, API compatibility checks, boundary test generation, and Monte Carlo risk simulation.
30+ deterministic dev and delivery tools: linting, metrics, diagrams, model advice, AI-text checks.
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
Repository knowledge graph MCP server for codebase understanding and debugging.
EU AI Act + GDPR compliance scanner. One call, no arguments, 10 seconds. 22 AI frameworks detected.
Multi-model code review: a panel of models + detectors return a pass/fail verdict. Paid via x402.
Architecture compiler for AI code. 11 tools, 92 actions, 872 Lean4 proofs, 100/100 self-cert.
Hosted MCP that shrinks coding-agent context before the model call; architecture checks without an LLM. Zero data retention.
The context platform for AI agents: code search, team decisions, and grounded project context.
Generate TIA Portal importable SimaticML (V19) from LadDoc IR, with strict validation, over MCP.
## 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
Founders' AI CSO: vulnerabilities, dependencies, secrets, verified-site checks, threat model, fixes.
