"Loop" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
Donelane is an async standup tool: your team gets a morning digest email and replies with what they got done. This MCP server puts your agents in that same loop. Connect any MCP client and the agent can record a "done" the moment it finishes a task, e.g. "Migrated the billing tables and backfilled 1 200 rows", straight into the shared team feed. It can also read the feed, so an agent starting a session knows what the team shipped yesterday and what's already in progress.
**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
Human-in-the-loop for AI agents over MCP: durable approvals with a hosted review page & audit trail
MCP-native AI SRE. Exposes your production OpenTelemetry problems, traces, and logs over the Model Context Protocol, plus an AI remediation loop that opens a reviewed GitHub fix PR and verifies in production (reopening on regression). Tools include list_problems, get_problem, query_traces, detect_anomalies, and request_problem_remediation. Human-in-the-loop by default — the merge button stays yours.
Deterministic regex synthesis from labeled examples. Zero LLM, proof matrix, backtracking audit.
Deterministic JSON repair, validate, example-gen, schema-coerce for agents. Zero LLM, sub-10ms.
Free dual MCP+agent registry. Probe Live, free demo, Kernel/Loop. Self-list + dual strategy.
Deterministic AI code review, with an audit record. Governance inside the agent loop.
Issue, rotate and revoke scoped API-key passes for 25+ providers — the agent never sees a real key
A paid remote MCP for Unity-MCP, built to return verdicts, receipts, usage logs, and audit-ready JSO
An MCP server that automatically collects feedback on your MCP server.
