"RAG MCP servers with quality validation" matching MCP tools:

• 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).

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• strale_execute

  Strale - 290+ API capabilities for AI agents

  Executes a Strale capability by slug and returns the result. Use this when you need to perform any verification, validation, lookup, or data extraction from the 271-capability registry. Call strale_search first to find the right slug and required input fields. Returns a result object with the capability output, quality score (SQS), latency, price charged, and data provenance. Five free capabilities work without an API key (10/day limit). Paid capabilities debit from the wallet — check strale_balance first for high-value calls.

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• search

  agent-tools (x402 directory)

  Find x402 / MCP services matching an intent or filter set. Two usage modes (agents pick whichever fits): A. Natural-language: `search(intent="fetch tweets for @user")` B. Pure browse: `search(has_mcp=True, category="defi", top_k=10)` At least one of `intent`, `category`, `chain`, `has_mcp`, `min_confidence` must be supplied — otherwise the call is rejected (we won't dump 2300+ rows). Results are ranked by: (health=ok AND tx_30d>0) → health=ok → has-quality-signal → confidence → tx_30d → recency. So the highest-quality real-traffic services appear first. Each item includes (when available): - confidence : 0.0–1.0 x402scan quality score. - tx_30d : 30-day x402 payment count (proxy for real usage). - match_snippet : FTS snippet showing where `intent` hit ([[token]]). - match_reason : list[str] of human-readable ranking signals. - mcp_url : populated when the service exposes an MCP endpoint (you can call it directly via streamable-http). Agents should prefer items with non-null confidence and tx_30d > 0 unless the user explicitly wants experimental endpoints. Args: intent: What the agent wants to do (English or Chinese). Optional when at least one structured filter is set. Synonym expansion covers twitter↔X↔推特, whale↔巨鲸, price↔价格 etc. top_k: Max services to return (default 5, hard cap 25). max_price_usd: Upper bound on per-call price in USD. category: Filter (see `list_categories`). chain: "base", "polygon", "solana", "arbitrum", ... min_confidence: Minimum confidence (0.0–1.0). 0.8+ keeps only services x402scan rates as high-quality. has_mcp: When true, return only services with a callable MCP endpoint. Use this when the agent wants to chain another MCP server rather than perform raw HTTP+x402.

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• group_discovery_scan

  DialogBrain

  Scan a group to evaluate its quality before joining. Fetches recent messages, analyzes activity, spam, and engagement, then returns a quality score and plain-English verdict. When to use: - After finding groups with group_discovery.search - Before deciding which groups to join Returns: overall_score (0-1), is_disqualified, disqualify_reasons, individual scores, and a verdict string.

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• search_mcp_servers

  Swarm Tips — Aggregated AI Agent Activities

  [IN DEVELOPMENT] [READ] Search the Layer 3 curated directory of MCP servers and agent-work tools. The directory has 30 entries across three vetting tiers — `first-party` (operated by the swarm.tips DAO), `vetted` (third-party, we've used + verified), `discovered` (cataloged from public sources, not yet exercised). Filter by `query` (substring vs name/description/tags), `category` (substring), and `tier`. Results sort first-party → vetted → discovered. The same directory powers swarm.tips/discover; this tool exposes it programmatically. Use this when an agent needs to find an MCP server for a capability (DeFi, search, browser automation, etc.) instead of an opportunity (which `discover_opportunities` covers).

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• generate_video

  Sats4AI - Bitcoin-Powered AI Tools

  Generate a video from a text prompt. Uses Kling v3 — cinematic quality, consistent motion, physics-aware rendering. Standard and pro quality modes with optional AI-generated audio track. Async — returns requestId, poll with check_job_status. Pricing: standard 300-400 sats/sec, pro 450-550 sats/sec (audio adds 100 sats/sec). Duration 3-15 seconds. Pay per request with Bitcoin Lightning — no API key or signup needed. Requires create_payment with toolName='generate_video' and duration, mode, generate_audio params.

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• 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")

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• get_adoption_stage

  Stratalize AI Governance Intelligence

  Public mode returns FS AI RMF framework reference data only — not org-specific scoring. Use when assessing an organization FS AI RMF governance maturity stage or preparing a regulatory AI roadmap presentation. Returns INITIAL, MINIMAL, EVOLVING, or EMBEDDED classification with stage criteria and remediation priorities. Example: EVOLVING stage organizations have documented AI policies but lack systematic model validation — typical gap to EMBEDDED is 18-24 months and 12-15 additional controls. Connect org MCP for org-specific scoring. Source: FS AI Risk Management Framework.

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• 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: "FDA analysis agents" → finds specialist agents with success rates - 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.

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• get_validation_framework

  Demand Discovery AI

  Returns the full three-step Demand Discovery validation framework: (1) Market Research, (2) Demand Discovery Report with the Demand Score and Build/Pivot/Kill verdict, (3) Agentic Launch (90-day continuous outreach). Use when a user asks "how do I validate an idea?", "what's the methodology?", or wants to understand the structured approach. Built on the "behavior over opinion" principle. Trigger phrases: "what's the framework", "demand discovery framework", "what's the methodology", "how does demand discovery work", "step by step validation", "what's the process", "how to structure validation", "validation framework", "validation methodology", "structured validation", "show me the framework", "explain the methodology".

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• lookup_paper

  BGPT - Scientific Paper Search

  Look up a single paper by its DOI. Args: doi: The DOI of the paper (e.g. "10.1038/s41586-024-07386-0"). api_key: Optional: Your Stripe subscription ID for paid access. Get one at https://bgpt.pro/mcp Returns: Paper with title, DOI, Raw Data, methods, results, quality scores, and 25+ metadata fields — or an error if not found. Costs $0.02 if found, free if not.

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• 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: "FDA analysis agents" → finds specialist agents with success rates - 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.

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• audit_taxonomy

  Velvoite — EU Financial Regulatory Compliance

  Audit the actor role taxonomy: compare model-defined roles vs deployed roles in the database. Returns per-regulation analysis showing: - model_only: roles the enrichment model can produce but aren't in the DB yet (gap) - deployed_only: roles in the DB but not in the model (unexpected — data quality issue) - role_counts: each deployed role with obligation count - known_issues: overlaps, naming issues, investigation items Use this for QA validation of the actor role taxonomy. Requires admin API key. No parameters needed — returns full corpus audit.

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• thinkneo_signup

  ThinkNEO Control Plane

  Sign up for ThinkNEO MCP free tier or retrieve current account if already authenticated. Idempotent: existing valid token returns current account info, no duplicate created. After signup, configure your MCP client with: Authorization: Bearer <api_key>

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• evaluate_service

  Agentic Platform

  Evaluate any MCP service for trustworthiness before spending money on it. Connects to the target server, checks reachability, governance declarations, tool definition quality, and audit endpoints. Returns a trust score from 0 to 100 with a recommendation: PROCEED, PROCEED WITH CAUTION, HIGH RISK, or DO NOT TRANSACT. No API key needed.

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• group_discovery_preview_messages

  dialogbrain

  Read recent public messages from a group without joining it. Only works for groups where can_preview_history=true. Use this to manually evaluate message quality before deciding to join. For an automated quality score, use group_discovery.scan instead. Returns: list of recent messages with sender, text, date, is_reply.

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• air_quality

  livedatalink

  Get current air quality data for any location. Returns US AQI index, PM2.5, PM10, ozone, NO2, SO2, and CO levels with health category rating. Use this for 'what's the air quality?', 'is it safe to go outside?', 'pollution levels', 'AQI in Los Angeles', 'should I wear a mask?', 'is there smoke in the air?', or any air quality or pollution question.

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• similar_to

  MCP Marketplace

  Find MCP servers that are semantically similar to a reference server. Use when a user picked a candidate but wants alternatives — e.g. 'like this but safer', 'like this but free', 'what else does this'. Reuses the catalog's gte-small embeddings: the reference server's embedding is the query vector. Returns servers sorted by cosine similarity (highest first), excluding the reference itself. Each result carries the same security/risk/pricing fields as search_servers so callers can immediately compare on `security_score`, `has_critical_findings`, and pricing.

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• get_briefing

  Ai Briefing

  Get today's AI tools briefing — new MCP servers, APIs, SDKs, frameworks from the last 24 hours. Returns release summaries with sources and descriptions. Use at session start.

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• chunk_text

  Toolora

  Use this tool to split long text into smaller, overlapping chunks suitable for embedding, vector storage, or RAG pipelines. Triggers: 'chunk this document for RAG', 'split this into embeddings', 'break this into segments', 'prepare this text for a vector database'. Returns an array of chunks with index, text, character count, and estimated token count. Essential before embedding or storing text in a vector database.

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