"Fetching data from an MCP server" 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.
An MCP server that compiles ASN.1 schema definitions into executable, native source code for a variety of languages (like Python, Rust).
Vet an agent skill before you install it: structure, triggers, secrets.
Security reviews, threat models over a repo or website, and remediation tracking, in your editor.
Smart-contract security audits for EVM chains and DAML: quote, run and fetch reports.
**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
Pine Script backtest-trap checks, backtest reconciliation and official Korean finance data.
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.
The official Svelte MCP server providing docs and autofixing tools for Svelte development
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.
Known vulnerabilities for exact package versions from OSV, with fixes. Paid per call, x402.
Compliance lint for AI, scraping, and privacy law. Cited findings in 200 or more jurisdictions.
Ask Void anything: answers with sources, plus code review, moon phases and meteor showers.
Stop your AI agents from writing sloppy TypeScript. A toolkit that teaches coding agents like Claude Code, Codex, Cursor, Amp, and more to ship production-ready code in half the time, at half the cost. Docs are available at https://convention.sh/docs
MCP server for YAML: validate & lint, convert between 10 formats, visualize as diagrams, and create/edit your saved diagrams — from your AI editor.
EU AI Act + GDPR compliance scanner. One call, no arguments, 10 seconds. 22 AI frameworks detected.
AI product expert answering from live source code, with sources and a verification status.
Pure, bounded analysis of an explicit bill-of-materials graph: validates structure, finds missing...
