"MiniMax MCP (Model Context Protocol) GitHub Repository" 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.
Coding agents in multi-service codebases routinely rebuild existing helpers, trust stale type definitions, and modify API contracts without knowing who consumes them. Carrick solves this by indexing your entire TypeScript ecosystem across service and repository boundaries. By integrating deeply with the TypeScript compiler, Carrick traces every route, type, and cross-service call while recording function behaviour so agents search by intent rather than name. Delivered via MCP for AI agents and LSP for IDEs, Carrick ensures models see existing endpoints and utilities before generating new code. The scanner is source-available and runs from your CLI or CI pipeline.
HefestoAI checks AI-generated code before you ship it.
Gives any public GitHub repo a safety grade (A to F) in plain English, with a clear next step: install, ask first, or don't install.
Safety grade (A to F) for any public GitHub repo, in plain English, before you install it.
30+ deterministic dev and delivery tools: linting, metrics, diagrams, model advice, AI-text checks.
Evaluates any GitHub repository for license risk, maintenance velocity, stars/forks, and supply-c.
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.
Free deterministic security scan of public git repos: OSV.dev vulnerable deps, secrets, config lint.
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
Hosted, OAuth-gated endpoint for quantakrypto's post-quantum crypto tools: scan code for quantum-vulnerable cryptography (RSA/ECDH/ECDSA/DH) and get NIST ML-KEM/ML-DSA/SLH-DSA migration guidance over authenticated HTTP — nothing to install. Sign-in required (Google/GitHub/email). Same tools as the open-source @quantakrypto/mcp server; source at github.com/quantakrypto/pqc-tools.
Recover project context, review recorded decisions, and steer queued work across AI coding agents.
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).
Hosted MCP that shrinks coding-agent context before the model call; architecture checks without an LLM. Zero data retention.
Stateless TypeScript and JavaScript code intelligence for AI agents. Find semantic symbol references, resolve imports and importers, inspect callers and callees, and analyze change impact with compiler-backed evidence. No repository indexing or OAuth required.
Dependency picker for coding agents: recommends, compares and scores GitHub repos with a verdict.
Scan GitHub-hosted AI skills for vulnerabilities: prompt injection, malware, OWASP LLM Top 10.
Ledger of record for AI spend: verifiable receipts, waste auditor & model arbitrage MCP.
LLM cost optimization gateway, repo token-waste auditor & model arbitrage MCP server.
Free security scan for AI-written GitHub repos: leaked keys, .env, eval, SQLi, CORS.
Known open GitHub issues in exact npm and PyPI versions, with workarounds, for coding agents.
Read-only scan of a public GitHub repo for leaked secrets, with a 0-100 grade.
Agentic code review, no signup to try: reality gates + frontier-model review, with veto.
Architecture diagrams, explanations and Mermaid source for public GitHub repositories.
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
Rams is a design reviewer for UI code. The MCP server puts the hosted engine inside a coding agent: the agent passes files to the review_files tool and gets back a 0–100 score with file:line issues and concrete fixes — accessibility, color, typography, spacing, components, UX, motion, craft, and native SwiftUI. Same engine and scoring as the Rams GitHub App. 258 rules, published at rams.ai/rules. Free tier: 30 reviews/month.
Repository knowledge graph MCP server for codebase understanding and debugging.
Scan any public GitHub MCP-server repo for security issues. 37 MCP-specific L1 rules, 8 languages.
Verify a vuln report's file/line/function claims against a real GitHub repo.
