"Information on agent swarm architecture" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
Your agent verifies its change before commit; PR review that knows what depends on your change.
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.
Find what to fix on a public website, for search engines and for AI answers.
Audits any live MCP server URL or GitHub repo on Glama's 6-dimension TDQS rubric and compiles dro.
Guardian agent for AI coding: four frontier models review risky diffs and commits before they ship.
Vet an agent skill before you install it: structure, triggers, secrets.
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.
**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.
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.
CodeSentinel — AI-powered codebase health agent
Give your AI agent a persistent map of your project's structure, dependencies, and bugs.
Audit AI Agent SDKs and MCP servers for breaking changes, schema drift, and migration fixes.
Scan AI agent skills, MCP server packages and MCP configs before you install them. Static analysis.
Generate and validate a .specs/ bundle for your repo, then hand it to your AI coding agent
Check code against secure-coding rules mapped to ISO 27001 and the DPDP Act. Free, no account.
Pre-flight verdict on MCP servers: known-bad identity, CVEs, dependency tree, tool drift. Signed.
Check an agent skill before you install it: which of your skills will it clash with?
Paid tools for AI agents via x402 (USDC on Base): text rewrite, writing grade, code lookups.
Architecture diagrams, explanations and Mermaid source for public GitHub repositories.
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?
Check if a dependency's license obligates you, based on how you ship. npm, PyPI, Go.
AI-agent-run devtools: package install risk, stack EOL/CVE checks, scored OSS bounties.
Honest library picks for coding agents in 25-360 tokens. Tells your agent what NOT to install.
Static linter for CLAUDE.md-style agent constitution files: 10 operational-guardrail checks.
