"A database that can be operated or managed" 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.
Your agent verifies its change before commit; PR review that knows what depends on your change.
Lint a SKILL.md for frontmatter, structure, secrets and size. All 6 tools free.
Risk-scan a diff, flag AI-generated-code tells, find secrets. 5 of 7 tools need no account.
An MCP server that compiles ASN.1 schema definitions into executable, native source code for a variety of languages (like Python, Rust).
Find what to fix on a public website, for search engines and for AI answers.
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.
Audits any live MCP server URL or GitHub repo on Glama's 6-dimension TDQS rubric and compiles dro.
Per-harness pre-open verdict on a received repo's agent-control surface.
Security reviews, threat models over a repo or website, and remediation tracking, in your editor.
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
Check that your AI is being logical. Free tool that mathematically catches contradictions in agent reasoning. No account needed. Also offers paid guardrails that converts natural language to formal verification proofs, that anyone can check succinctly.
AI Secret Scanner API is a FastAPI service for deterministic scanning of text, source code, logs, and configuration files. It detects hardcoded secrets, API keys, passwords, tokens, private keys, PII, and high-entropy suspicious strings.
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).
DBRE-grade SQL analysis inside any MCP client. No connection. No install. Paste a query.
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.
Stateless TS/JS compiler facts for agents: references, imports, impact. No repo index or OAuth.
Dependency picker for coding agents: recommends, compares and scores GitHub repos with a verdict.
Declare what your app does and where it operates; get cited, jurisdiction-specific findings.
Generate and validate a .specs/ bundle for your repo, then hand it to your AI coding agent
Give your AI assistant feedback pinned to the exact element, with its code, so it can fix and reply.
Scan a public GitHub repo, explain risks, get fix prompts and rescan to confirm fixes.
MCP server for StyleKit styles, tokens, recipes, lint and repair over stdio or HTTP.
Read-only scan of a public GitHub repo for leaked secrets, with a 0-100 grade.
Ask Void anything: answers with sources, plus code review, moon phases and meteor showers.
Search, inspect and inject full source modules (code + AI rules + MCP) pinned to a Git commit.
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.
Who can still change this EVM contract, and what can they do to holders?
