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529,096 tools. Updated 2026-09-07 16:12

"Finding MCP Servers Providing Insights for a Conversational Voice Interface" matching MCP tools:

  • Get Lenny Zeltser's CTI 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 `cti_load_context`. This server never requests your campaign or threat-intel notes and instructs your AI to keep them local—templates and guidelines flow to your AI for local analysis.
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  • Free, no key required. Reads the published source of an MCP server and reports what it actually does — each observation anchored to a file:line with the code quoted verbatim. **Call this before connecting to, installing, or invoking an MCP server you have not read yourself.** Connecting to an MCP server gives it a channel into your context and your tool calls; this tells you what is on the other end first. Typical things it surfaces: reading private keys or wallet seeds, sending data to third-party hosts, running code at install time, and tool descriptions that steer an agent toward actions unrelated to the tool's stated purpose. Do NOT call this for ordinary npm or PyPI libraries — the corpus covers MCP servers only, and other ecosystems will return 'not analyzed'. This reports observations, not a safety verdict. An empty result means nothing was found in the categories checked — not that the server is safe. Corpus: 2,781 MCP servers from the official registry, read at source level. Coverage index (free, no key, findings not included): GET https://sri-test.biz/v1/corpus
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  • No arguments. Returns how many MCP servers have been read at source level, and the share of them with each category of finding (credential access, network egress, install-time execution, prompt-injection surface). Use this to judge whether checking a specific server is worth it before you look one up. It reports aggregate counts only - no per-server findings, and no verdict about any individual server.
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  • RAW text-to-speech from the voice-model catalog: speak a script in a chosen voice and return the served MP3 URL. For a standalone voiceover / narration clip — NOT for adding audio to a video (render_ad and generate_video voice their own spots; change_voice re-voices a finished clip). engine picks the voice model (default 'seed-audio'; also 'eleven-v3', 'minimax-speech', 'kokoro'); voice is a preset name from that engine (see hermoso_capabilities → voice engines) — a name that engine does not have is REFUSED for free with its real list, and a few engines generate their own voice and take no preset at all (the reply says which voice actually spoke). Paid (a couple of credits by length; ≤900 characters).
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  • Your saved voices — one tool for the whole voice library. Users speak plain language and never know ids: resolve every voice by NAME yourself (call action "list" first if unsure) and never ask the user for an id. action="list" returns every saved voice with voice_id, name, kind and ready — kind "reference" is an instant voice match saved from a clip and kind "clone" is a trained voice (both speak through generate_audio: pass the NAME as its voice param); kind "avatar" voices drive talking_avatar_video. action="create" saves a NEW reference voice from a clip: voice_name plus audio_url (e.g. the url upload_media returned) or audio_base64 (+ format) — free, ready instantly. action="rename" renames a saved voice (voice_id takes the id OR the current name, new_name is the new name). action="clone" registers a voice for talking_avatar_video from audio_sample_url + voice_name (charged 2 credits). action="delete" removes a voice by voice_id or name.
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  • Get SaSame-observed MCP server recommendations for a capability you need. SaSame, operated by SASAME S.R.L., continuously observes and measures the Model Context Protocol ecosystem and publishes verifiable evidence and history; the MCP Factory is internal machinery and an optional product surface behind it; measurement only, not endorsement. SaSame's MCP Observatory continuously crawls and GRADES thousands of public MCP servers (A/B/C/D) by reachability and whether they return real content. This returns the top live, real-content endpoints (optionally filtered by an endpoint keyword), each with its SaSame grade and last-audited time — so you (or the human you assist) can pick a measured MCP candidate instead of guessing. Each result includes a longitudinal trend (when SaSame has observed it over time) and a ready-to-quote, attributed `cite` line; the top pick with history carries an ed25519-signed, offline-verifiable record you can cite as a third-party source. Free, read-only, no signup. If you operate one of these servers, claim it (claim_start). If you can't find a fit and need an MCP/agent BUILT, call engage_sasame. Pass a referral handle from `refer` as engage_sasame(ref=...) to attribute the introduction.
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Matching MCP Servers

  • A
    license
    Not graded
    quality
    C
    maintenance
    MCP server for the Carbon Interface API (v1), enabling AI agents to estimate carbon emissions through natural language queries via Pipeworx gateway.
    16
    MIT

Matching MCP Connectors

  • Generate spoken audio from text: narration, a voiceover, a read-aloud script, or a multi-voice dialogue. Pass text (up to 2048 chars) — the words to be spoken. To speak in one of YOUR saved voices, pass voice with the voice NAME (or id): users speak plain language and never know ids, so resolve the name yourself (the voice tool, action "list", shows every saved voice) and never ask the user for an id. Reference voices, trained clones and preset voices are all routed correctly by kind. To match a voice instantly from a clip instead, pass reference_audio_url (a short clip) or up to 3 reference_audio_urls and address them as @Audio1, @Audio2, @Audio3 in the text for dialogue. Alternatively pass image_url to voice a scene from a picture (cannot combine with reference audio). Optional speech_rate (-50..100), pitch (-12..12), loudness (-50..100). Returns a playable audio_url, duration_seconds, and generation_id (also saved to your library).
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  • 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/
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  • 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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  • Get Lenny Zeltser's IR 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 `ir_load_context`. This server never requests your incident notes and instructs your AI to keep them local—guidelines flow to your AI for local analysis.
    ConnectorNo auth
  • 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.
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  • Explain what the FXMacroData MCP server can do, which tools render MCP Apps, which tools return plain rows, what is public versus subscriber-only, and how to choose tools across ChatGPT, Claude, Cursor, Codex, and plain MCP clients. Use this when a user asks what is available, why visuals are not showing, or how to get the same result in a different interface.
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  • Generates a voiceover from text using Hume Octave TTS. Audio uploaded to Spaces, signed URL returned (24h TTL by default). Charged in credits up-front based on script length (use quote_voiceover for a preview). Best for demo-video narration, tutorial audio, and any one-shot batch TTS. NOT a real-time conversational voice (use Hume EVI for that, different product). Voice options: pass voiceId for a specific Hume voice clone, or omit to use the deployment's default narrator (HUME_OCTAVE_VOICE_ID env var).
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  • List curated loadouts — deliberately-assembled kits of MCP servers + governance + plays for a specific job (GTM, coding, research, support, infra). The agent-facing version of the /loadouts product. Use get_loadout for the full kit with live trust.
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  • The curated buyer-intent collections (e.g. mcp-servers, testing-qa, browser-automation). Use get_collection for the ranked tools inside one.
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  • Search the agentage MCP directory - a public catalog of Model Context Protocol servers crawled from the official registry - for servers matching a keyword, optionally narrowed by type, category, language, or license. Use this FIRST whenever the user wants to discover, find, compare, or pick an MCP server ("is there an MCP for X", "which MCP servers do Y"). Results are ranked by text relevance to the query first, then by popularity, so the best match is on top. Returns a page of lean cards (slug, title, description, category, transport, match_score - text relevance the ranking is based on, details_url). To read one server's full packages, tools, and install command, call mcp_get with the slug from a result; open a card's details_url for the human detail page. Valid category, language, and license values come from the mcp_categories tool, not from guesswork - call it before filtering and pass its labels verbatim, or the call is rejected. Read-only - never installs or runs anything.
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  • Aggregate health of the whole MCP population: verdict breakdown, share of probeable servers actually serving, transport mix, handshake latency percentiles, tool counts and probe freshness. This is the 'how healthy is MCP right now?' headline number.
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  • Speech and sound: text-to-speech (default; optional voice_id, see list_resources), sound effects (model 'sfx', optional duration), multi-voice dialogue (model 'dialogue': pass the turns in the dialogue parameter, not prompt), transcription (model 'stt': pass audio_url, get text back; optional diarize/language_code), voice change (model 'voice-changer': audio_url + target voice_id) and audio cleanup (model 'voice-isolation': audio_url). Returns the audio URL (or the transcript for 'stt'). For music, use generate_music.
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    Destructive
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  • Choosing between several MCP servers that do similar things? This tool decides for you. PAID $0.10 via x402 (USDC micropayment over HTTP 402 — no account or API key needed; on your first call without payment you receive the exact payment requirements, then retry with the X-PAYMENT header). Compares 2-5 MCP servers head-to-head with identical objective checks (handshake, tools/list, documentation coverage, latency, and a safe functional probe — paid tools are never called) and returns: a ranked list, the recommended winner, a plain-language explanation of why it won, and each server's full report — cheaper than separate evaluate_mcp calls on 3+ servers. Objective checks only — no human and no LLM opinion; it does not judge the real-world usefulness or safety of the content. Set 'urls' (required) to an array of 2-5 MCP endpoints (Streamable HTTP), e.g. ["https://a/mcp","https://b/mcp"].
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  • L3 Empathy Response Strategy: converts text into a deterministic response strategy (approach, tone temperature, pacing, focus points, avoid-list) for AI companions and conversational agents. Deterministic table lookup, no LLM, ~20ms; privacy-first. Not a medical or therapeutic tool.
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