"Informational MCP Servers with Croissant Dataset Format Support" matching MCP tools:

• query_registry

  Arclan MCP Registry

  Search the Arclan registry for MCP servers. By default returns only connectable servers (active, mcp_partial, auth_gated). Use status=stdio to browse local-only servers available for installation. Use status=all to query the full index. Use production_safe=true to restrict to servers with uptime > 97% and handshake success > 95%. Use read_only=true to restrict to servers with no write or exec tools. Use this before connecting to an MCP server to check its validation status and score. After using a server, call report_server to contribute reliability data.

  Connector

• ateam_redeploy

  ateam-mcp

  Re-deploy skills WITHOUT changing any definitions. ⚠️ HEAVY OPERATION: regenerates MCP servers (Python code) for every skill, pushes each to A-Team Core, restarts connectors, and verifies tool discovery. Takes 30-120s depending on skill count. Use after connector restarts, Core hiccups, or stale state. For incremental changes, prefer ateam_patch (which updates + redeploys in one step).

  Connector

• switch_dannet_server

  dannet

  Switch between local and remote DanNet servers on the fly. This tool allows you to change the DanNet server endpoint during runtime without restarting the MCP server. Useful for switching between development (local) and production (remote) servers. Args: server: Server to switch to. Options: - "local": Use localhost:3456 (development server) - "remote": Use wordnet.dk (production server) - Custom URL: Any valid URL starting with http:// or https:// Returns: Dict with status information: - status: "success" or "error" - message: Description of the operation - previous_url: The URL that was previously active - current_url: The URL that is now active Example: # Switch to local development server result = switch_dannet_server("local") # Switch to production server result = switch_dannet_server("remote") # Switch to custom server result = switch_dannet_server("https://my-custom-dannet.example.com")

  Connector

• fetch

  Penfield Memory

  [ChatGPT Connector compat] Fetch memory by ID. Exists to satisfy ChatGPT Deep Research's required `search`/`fetch` tool contract. Native MCP clients should fetch via `recall` + memory_id, or use the API's GET /memories/{id} endpoint directly. Returns a single memory with citation support (id, title, url, text fields). Args: id: Memory UUID to fetch ctx: MCP context Returns: Dict with id, title, url, text, metadata fields

  Connector

• pool_block

  PoolParty Main Stage Airtime

  Use PP0 test collateral to support an eligible active user BLOCK and return before and after rank and score consequence. Creates a STAKE_ADD transaction intent or explicit local/mock rehearsal state. In Amoy prepare mode, submit the returned wallet transaction and then call finalize_pool_support with the tx hash before treating support as active. Settlement is inspected later through get_pooling_receipt and get_block_economics. Public wallet action. No MCP auth required, but wallet-owner approval or an agent-owned funded wallet signer is required for Amoy transactions.

  Connector

• search_mcp_servers

  agent-tools (x402 + MCP + A2A directory)

  Find MCP servers in the directory. Searches the standalone MCP directory (PulseMCP / official MCP registry import) unioned with x402 services that also expose an MCP endpoint. Returns normalised entries with a ready-to-use streamable-http `call_hint.mcp.url`. Args: intent: Natural-language description of the tool/capability needed. top_k: Max servers to return (1-20). chain: Optional payment-network filter for paid MCP servers. require_healthy: When true, only return servers marked health=ok.

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• search_datasets

  Nova Scotia Data Explorer

  Search the Nova Scotia Open Data catalog (data.novascotia.ca) for datasets by keyword, category, or tag. Returns dataset names, IDs, descriptions, column names, and direct portal links. Use list_categories first to see valid category and tag names. Use the returned dataset ID with query_dataset or get_dataset_metadata for further exploration.

  Connector

• licium_discover

  Licium

  Browse and compare Licium's agents and tools. Use this when you want to SEE what's available before executing. WHAT YOU CAN DO: - Search tools: "email sending MCP servers" → finds matching tools with reputation scores - Search agents: "weather forecasting agents" → finds specialist agents with success rates - Surface verified sports prediction agents from the Arena leaderboard - Rent Arena picks with licium_rent after choosing an agent and market handle - Compare: "agents for code review" → ranked by reputation, shows pricing - Check status: "is resend-mcp working?" → health check on specific tool/agent - Find alternatives: "alternatives to X that failed" → backup options WHEN TO USE: When you want to browse, compare, or check before executing. If you just want results, use licium instead.

  Connector

• mock_from_schema

  IA-QA — 130+ QA & Dev Tools for AI Agents

  Generate realistic mock data from a JSON Schema. Supports all common types (string, number, integer, boolean, array, object, null), format hints (email, date, date-time, uri, uuid), enum, const, and nested schemas. Perfect for testing MCP tools with realistic data.

  Connector

• cyanheads_search

  cyanheads-mcp-server

  Search fleet tools and servers by natural-language description. Returns ranked matches with brief summaries and the server each tool belongs to. Use scope "servers" to find which server handles a workflow; use the default scope "tools" to find specific tools. Call cyanheads_describe on a result name to get install snippets and the connection URL.

  Connector

• dataset_details

  Opendata Swiss

  Full metadata for one dataset (CKAN package_show) including its resources/distributions with download URLs. Use a dataset `name` (slug) or id from search_datasets. There is no datastore, so fetch `resources[].download_url`/`url` for the underlying data.

  Connector

• malware_get_cross_server_routes

  website-search

  Get Lenny Zeltser's Malware cross-server handoff routes — when this MCP server can't fulfill a request, which other MCP servers (or fallback workflows) to consult. Surfaces a compact subset of `malware_load_context`. This server never requests your sample, analysis notes, or indicators and instructs your AI to keep them local—guidelines and the report template flow to your AI for local analysis.

  Connector

• assessment_get_cross_server_routes

  website-search

  Get Lenny Zeltser's Security Assessment cross-server handoff routes — when this MCP server can't fulfill a request, which other MCP servers (or fallback workflows) to consult. Surfaces a compact subset of `assessment_load_context`. This server never requests your assessment notes or report and instructs your AI to keep them local—the templates and guidelines flow to your AI for local analysis.

  Connector

• seneschal_agent_directory

  Seneschal

  Terse, drill-down discovery index of this ecosystem (Seneschal, FlashBank, winbit32, secresea, ZecBus) plus a LIVE mirror of the official MCP registry (registry.modelcontextprotocol.io) — the same directory served over HTTPS at https://seneschal.space/.well-known/agent.gopher, callable here so you never leave the MCP session. Start with section="root" to see the top-level menu, then call again with section="seneschal"/"flashbank"/"winbit32"/"secresea"/"zecbus" to drill into a project. Each project exposes About / Agents / Actions — drill them with section="<site>/about", "<site>/agents" or "<site>/actions" (e.g. "winbit32/actions"). Seneschal additionally drills into its own services with section="seneschal/<service>" where <service> is one of private-watch, checkout, oracle, shovels, builder, data, paymaster, board, ironwood, mcp — every website + MCP capability, grouped and priced. section="registry" browses connectable third-party MCP servers (use `cursor` to page); section="about"/"agents" is the directory’s own prose. format="gopher" (default) is the compact RFC-1436 menu; format="json" returns a structured {title, items[]}. A discovery layer, not a replacement for MCP — use it to FIND tools, then connect. Free, no payment.

  Connector

• seneschal_agent_directory

  Seneschal Data

  Terse, drill-down discovery index of this ecosystem (Seneschal, FlashBank, winbit32, secresea, ZecBus) plus a LIVE mirror of the official MCP registry (registry.modelcontextprotocol.io) — the same directory served over HTTPS at https://seneschal.space/.well-known/agent.gopher, callable here so you never leave the MCP session. Start with section="root" to see the top-level menu, then call again with section="seneschal"/"flashbank"/"winbit32"/"secresea"/"zecbus" to drill into a project. Each project exposes About / Agents / Actions — drill them with section="<site>/about", "<site>/agents" or "<site>/actions" (e.g. "winbit32/actions"). Seneschal additionally drills into its own services with section="seneschal/<service>" where <service> is one of private-watch, checkout, oracle, shovels, builder, data, paymaster, board, ironwood, mcp — every website + MCP capability, grouped and priced. section="registry" browses connectable third-party MCP servers (use `cursor` to page); section="about"/"agents" is the directory’s own prose. format="gopher" (default) is the compact RFC-1436 menu; format="json" returns a structured {title, items[]}. A discovery layer, not a replacement for MCP — use it to FIND tools, then connect. Free, no payment.

  Connector

• list_sectors

  Austrian Firmenbuch

  Valid filter values for search_companies, with company counts. Read-only, no parameters. Returns the legal-form (Rechtsform) codes and the size-class (`gkl`: W/K/M/G) values present in the served dataset, each with its count. Call this first to discover the real `legal_form` / `size_gkl` values to pass to search_companies or get_cohort_summary, instead of guessing codes. For region/format coverage instead, use get_coverage.

  Connector

• scan_mcp

  Hlido Agent Reviews

  On-demand independent SAFETY scan of an MCP server — call this BEFORE installing or connecting to one. Give it an HTTP(S) MCP endpoint URL (scanned live in seconds), or an npm/PyPI package name or GitHub repo (queued for an isolated sandbox scan — local stdio servers execute code, so Hlido never runs them inline). Returns the safety tier (SAFE/CAUTION/RISKY/DANGEROUS), tool-poisoning detection (the malice signal), dangerous-capability red-flags (shell/code-eval/fs-write/egress/secrets) with per-tool evidence, and auth posture. Tier = blast radius if hijacked, not maintainer trustworthiness. A server Hlido hasn't scanned returns not_scanned — never assumed safe. Register of already-scanned servers: https://hlido.eu/mcp/

  Connector

• search_datasets

  Nova Scotia Data Explorer

  Search the Nova Scotia Open Data catalog (data.novascotia.ca) for datasets by keyword, category, or tag. Returns dataset names, IDs, descriptions, column names, and direct portal links. Use list_categories first to see valid category and tag names. Use the returned dataset ID with query_dataset or get_dataset_metadata for further exploration.

  Connector

• export_dataset

  Trillboards DOOH Advertising

  Export observation data as a structured dataset. Supports filtering by time, geography, venue type, and observation family. Applies k-anonymity (k=5) to protect individual privacy. Queries the relevant table based on the selected dataset type, applies filters, enforces k-anonymity by suppressing groups with fewer than 5 observations, and returns structured data. WHEN TO USE: - Exporting audience data for external analysis - Building datasets for machine learning or reporting - Getting structured vehicle or commerce data for a specific time/place - Creating cross-signal datasets for correlation analysis RETURNS: - data: Array of dataset rows (schema varies by dataset type) - metadata: { row_count, k_anonymity_applied, export_id, dataset, filters_applied, time_range } - suggested_next_queries: Related exports or analyses Dataset types: - observations: Raw observation stream data (all families) - audience: Audience-specific data (face_count, demographics, attention, emotion) - vehicle: Vehicle counting and classification data - cross_signal: Pre-computed cross-signal correlation insights EXAMPLE: User: "Export audience data from retail venues last week" export_dataset({ dataset: "audience", filters: { time_range: { start: "2026-03-09", end: "2026-03-16" }, venue_type: ["retail"] }, format: "json" }) User: "Get vehicle data near geohash 9q8yy" export_dataset({ dataset: "vehicle", filters: { time_range: { start: "2026-03-15", end: "2026-03-16" }, geo: "9q8yy" } })

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• request_introduction

  TESSA Marketing & Technology

  Request an informational introduction — to TESSA itself, or to any directory firm if you pass target_firm_slug. TESSA logs the lead and either notifies sales@tessa.tech + kevincallen@tessa.tech (TESSA leads) or forwards a warm intro email to the firm with TESSA Cc'd (directory leads). No calendar booking — use request_strategy_session to book a meeting with TESSA.

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