"GPT-SoVITS MCP (Model Context Protocol) Integration" matching MCP tools:

• count_tokens

  ToolSnap MCP

  Estimate the number of tokens a text will consume when sent to an LLM. Uses a byte-pair encoding approximation compatible with cl100k_base (GPT-4, Claude, and most modern models). Accurate to ±10% on English prose. Returns token count, character count, byte count, and a cost estimate footnote. Does NOT send text to any LLM — estimation is purely local. Has no side effects. Free. Use before sending long context to an LLM to avoid surprises. Do NOT use to count characters or words — use text_stats instead.

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• score_prompt

  pqs-mcp-server

  Score a prompt's quality across 8 dimensions BEFORE sending it to an expensive model. Returns a 0-80 score, an A-F grade, the per-dimension breakdown (clarity, specificity, context, constraints, output_format, role_definition, examples, cot_structure), and the weakest dimension. USE WHEN: - The user is workshopping a prompt and asks "is this good?" / "will this work?" / "should I add more detail?" - The user is about to send a long or expensive prompt to GPT-4, Claude Opus, or any frontier model, especially in a batch or automation context where rework is costly. - The user mentions iterating on a prompt that produced poor output and wants to diagnose what's missing. - The user pastes a prompt and asks for feedback on it. DO NOT USE WHEN: - The user is asking you to write a prompt for them (write it yourself first, then optionally call score_prompt to verify). - The prompt is conversational chat (this scores task-shaped prompts). COST: Free, no API key required. Rate-limited per IP: 5/min, 10/day, 100/month. If the user exceeds the limit, the response will include a structured upgrade path with subscribe and account URLs. LATENCY: ~2 seconds.

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• analyze_company

  Nordic Financial MCP

  AI-powered company analysis using semantic search over Nordic financial data. Orchestrates multiple searches internally and returns a synthesized narrative answer with source citations. Covers annual reports, quarterly reports, press releases and macroeconomic context for Nordic listed companies. Use this when you want a synthesized answer rather than raw search chunks. For raw data access, use search_filings or company_research instead. For a full due diligence report with AI-planned sections, use the Alfred MCP server: alfred.aidatanorge.no/mcp Args: company: Company name or ticker question: What you want to know about the company model: 'haiku' (default) or 'sonnet'

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• search_knowledge

  AlgoVault — Crypto Quant Trade Calls

  Returns ranked snippets from the AlgoVault knowledge bundle answering a question about its MCP tools, response shapes, integration patterns (LangChain, LlamaIndex, MAF, CrewAI), or code examples. Call this BEFORE other tool calls to confirm parameter usage and avoid hallucinating tool shapes. Fast: BM25 lexical search, no LLM call, no quota cost. For a synthesized natural-language answer use chat_knowledge. Read-only, no side effects.

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• aetherwave_generate_image

  AetherWave Studio

  Generates one or more images from a text prompt (T2I) or a text prompt + reference image(s) (I2I). Submits the job, polls until terminal, and returns the final image URLs. Default model is 'grok-imagine-t2i' (fast, 6 images per generation, 5 credits). Use list_image_models to see the full lineup with pricing. For I2I, pass `referenceImages` as an array of public image URLs and pick a model with I2I support (e.g. 'grok-imagine-i2i', 'wan-2.5-spicy-i2i'). ## Model selection guide (when the user does not specify a model) Default: `grok-imagine-t2i` (5 cr, 6 outputs per call, fast, general purpose). **Strong recommendation: when a single high-quality output is what's wanted** (most agent / one-shot workflows), prefer `gpt-image-2-t2i` (9 cr @ 1K / higher @ 2K, single deterministic image, best general quality across realism, illustration, typography, and composition; supports up to 2K resolution and most aspect ratios including auto). This is the front-runner for serious creative output where you don't need to pick from 6 variations. Pick a different model when the prompt has these signals: - "single best result" / "one image" / production / no time to pick from variations -> `gpt-image-2-t2i` (9 cr, 1 output, top general quality) - "photoreal" / "photo of" / "realistic" -> `gpt-image-2-t2i` (9 cr, best general realism) or `imagen-4` (12 cr, very high quality) or `z-image-turbo` (3 cr, fastest) - "highest quality" / "premium" / no budget -> `gpt-image-2-t2i` at 2K, or `grok-imagine-quality-t2i` (16 cr @ 1K, 22 cr @ 2K), or `imagen-4-ultra` - Text inside the image (signs, posters, typography) -> `ideogram-v3-t2i` (best in class) or `gpt-image-2-t2i` (also strong) - Artistic / painterly / stylized -> `midjourney-t2i` - Album art / cover art -> `gpt-image-2-t2i` for one strong image; `grok-imagine-t2i` for 6 variations to choose from; `seedream-v4-t2i` if 4K wanted - Logo or design with embedded text -> `ideogram-v3-t2i` - NSFW / adult / explicit -> `wan-2.5-spicy-t2i` (auto-tags creation as 18+; routes to adult gallery) - Cheapest possible / quick test -> `z-image-turbo` (3 cr) - Multiple variations to compare -> keep `grok-imagine-t2i` (6 outputs default) or use `numImages` on a multi-output model For I2I (reference image provided): prefer the dedicated `aetherwave_edit_image` tool for "change something in this image" intent. Use `aetherwave_generate_image` with I2I models only when you specifically want style transfer (`midjourney-i2i`), premium quality (`grok-imagine-quality-i2i`), or adult content (`wan-2.5-spicy-i2i`). Always pass an explicit `aspectRatio` (e.g. "1:1" for square album art, "16:9" for video thumbnails, "9:16" for shorts/reels). Some upstream providers reject submissions with no aspect ratio. Ask the user only when: - The prompt contradicts itself (e.g., "highest quality but cheapest") - The user requested "the best model" with no context, surface 2-3 options with tradeoffs - A single generation would cost more than 20 credits and the user has not confirmed

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• aetherwave_edit_image

  AetherWave Studio

  Edits an existing image guided by a text prompt. Pass a public `imageUrl` plus a `prompt` describing the change ("add a moon to the sky", "swap the background for a neon city", "make it look like a comic panel"). Submits, polls, and returns the edited image URL(s). Default model is 'grok-imagine-i2i' (6 cr per call, returns 2 variations, ~30s, best cost-to-quality on standard edits). Other I2I-capable models: 'seedream-v4-edit', 'wan-2.5-spicy-i2i', 'flux-kontext-pro', 'qwen-image-edit', 'gpt-image-1.5-i2i' (slow, ~5min). Use list_image_models for full lineup. Note: source URLs with spaces or parentheses may fail upstream; prefer clean URLs. ## Model selection guide for edits Default: `grok-imagine-i2i` (6 cr per call, returns 2 variations = 3 cr/image effective, fast ~30s, strong general-purpose edit quality). Pick a different model when: - Need a single deterministic output, or 4K resolution -> `seedream-v4-edit` (7 cr per image, supports 1K/2K/4K, multi-image up to 6) - Subtle edits / preserve composition / character consistency -> `flux-kontext-pro` or `flux-kontext-max` - NSFW edits -> `wan-2.5-spicy-i2i` - Highest quality, time is not a concern (~5 min OK) -> `gpt-image-1.5-i2i` or `grok-imagine-quality-i2i` (16 cr @ 1K, 22 cr @ 2K) - Stylized / artistic transformation -> `midjourney-i2i` If the user simply says "edit this image" with no other signal, default to `grok-imagine-i2i`.

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• 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

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• register_agent

  Arcology Knowledge Node

  Register as an agent to get an API key for authenticated submissions. Registration is open — no approval required. Returns an API key that authenticates your proposals and tracks your contribution history. IMPORTANT: Save the returned api_key immediately. It is shown only once and cannot be retrieved again. Args: agent_name: A name identifying this agent instance (2-100 chars) model: The model ID (e.g., "claude-opus-4-6", "gpt-4o")

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• score_prompt

  PQS - Prompt Quality Score

  Score a prompt's quality across 8 dimensions BEFORE sending it to an expensive model. Returns a 0-80 score, an A-F grade, the per-dimension breakdown (clarity, specificity, context, constraints, output_format, role_definition, examples, cot_structure), and the weakest dimension. USE WHEN: - The user is workshopping a prompt and asks "is this good?" / "will this work?" / "should I add more detail?" - The user is about to send a long or expensive prompt to GPT-4, Claude Opus, or any frontier model, especially in a batch or automation context where rework is costly. - The user mentions iterating on a prompt that produced poor output and wants to diagnose what's missing. - The user pastes a prompt and asks for feedback on it. DO NOT USE WHEN: - The user is asking you to write a prompt for them (write it yourself first, then optionally call score_prompt to verify). - The prompt is conversational chat (this scores task-shaped prompts). COST: Free, no API key required. Rate-limited per IP: 5/min, 10/day, 100/month. If the user exceeds the limit, the response will include a structured upgrade path with subscribe and account URLs. LATENCY: ~2 seconds.

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• list_paired_models

  ReliaStats

  Return the catalog of paired models — concrete real-world systems that live in two ChiAha sandboxes simultaneously, one for dynamics (DES via ReliaSim) and one for statistics (distribution fitting + validation via ReliaStats). Today: a single paired model — the bottling line. Returns canonical model IDs + cross-MCP routing metadata (which ReliaSim chapter, which ReliaSim MCP tools, which ReliaStats mode consumes which file shape). Use when a user asks about cross-MCP workflows, paired sandboxes, or the bottling-line example. ANTI-FABRICATION: this is a soft-reference catalog — to actually run a simulation, the LLM client calls ReliaSim's MCP tools directly.

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• get_embedder_network_manifest

  storyflo

  Wrap the public ``/embed/network-manifest.json`` — the platform-level DSP/SSP onboarding bundle: supported creative formats, payout rails, attribution URLs, integration patterns. Use when an agent is evaluating whether to wire storyflo into its surface, or when a DSP partner needs the canonical integration shape. Public — no auth required.

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• compare_protocols

  Intelligence MCP

  Get a side-by-side comparison matrix of all five agent payment protocols (AP2, ACP, x402, MPP, UCP) across creator, layer, agent delegation, budget limits, cross-merchant coordination, and MCP integration. Use when the user asks to compare protocols ('AP2 vs ACP', 'which protocol handles budgets?', 'what's the difference between x402 and MPP?', 'show me the landscape'). Use get_protocol_info instead for deep details on a single protocol.

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• compare_protocols

  intelligence-mcp

  Get a side-by-side comparison matrix of all five agent payment protocols (AP2, ACP, x402, MPP, UCP) across creator, layer, agent delegation, budget limits, cross-merchant coordination, and MCP integration. Use when the user asks to compare protocols ('AP2 vs ACP', 'which protocol handles budgets?', 'what's the difference between x402 and MPP?', 'show me the landscape'). Use get_protocol_info instead for deep details on a single protocol.

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• info_platformmetrics_get_platform_info

  Gate Info MCP

  One-shot protocol profile by name and scope. scope=full adds competition_metrics{} for CEX venues (spot/derivs/depth/OI core+extended/PoR). Set include_oi_symbol_detail=true with oi_symbol_limit (1-100, default 20) for top-N OI breakdown. Ranked multi-protocol list→search_platforms. Daily time series→get_platform_history.

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• audit_comp_live_listings

  CIPHER x402 — Paid Solana & Crypto Tools

  Return a curated snapshot of currently-live audit competitions and bug-bounty programs across Code4rena, Cantina, Sherlock, and direct-protocol channels. Useful for solo wardens triaging which contests to enter. Snapshot updates with each cipher-x402-mcp release; treat the data as a hint, always cross-check the platform before submitting. Free, no payment required.

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• prepare_consult_domain_expert

  Taste

  Get a humantaste.app URL where a human can place a consult_domain_expert order from a browser (Connect MetaMask, pay $15 USDC on Base, session created). Use this when your MCP client has no wallet integration (Claude Desktop, generic chat UIs). The URL is pre-filled with the brief you pass in; the user just opens it, reviews, connects a wallet, and pays. Returns the payment URL and the price. Free.

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• search_ai_models

  dynamic-feed

  Search current AI models by price, context window, and capability. Use this for up-to-date model pricing/features you don't reliably know. Prices are USD per 1M tokens. Results are cheapest-input-price first. Args: query: match part of a model name/id (e.g. "haiku", "gpt"). provider: filter to one provider (openai, anthropic, google, xai, mistral, deepseek, groq). max_input_price: only models at or below this USD/1M input price. min_context: only models with at least this context window (tokens). needs_vision: only models that accept images. limit: max results. Envelope: this searches our model-pricing registry, so measured_at = when the freshest matching row was last refreshed (each row's `updated_at`); max_age 18h covers the 12h registry-refresh cycle so a current row never falsely reads "stale". A search returning nothing yields unavailable — there's no honest observation time to claim.

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• get_platform_info

  mcp

  Get high-level facts about the ACCRUE platform: fee structure, custody model, supported chains, wallets, KYC requirements, withdrawal terms, and AI agent integration status. Use this when the user asks "what is ACCRUE", "how does ACCRUE work", "what are the fees", or anything about the platform itself rather than a specific vault.

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• integrations_add_endpoints

  dialogbrain

  Add one or more API endpoints to an HTTP-API integration as callable tools, merged additively into the integration for `base_url` (created if none exists). Each endpoint becomes a tool with params + request/response schemas inferred from the samples you pass. Supply `identity` (saved Browser Identity name/id) only when creating a brand-new integration; updates keep the existing auth. Returns the new tool count and names. Refresh the tools list afterwards to use them.

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• set_ens_records

  Name Whisper — ENS Intelligence Layer

  Set ENS resolver records for a name you own. Returns encoded transaction calldata ready to sign and broadcast. Supports address records (ETH, BTC, SOL, etc.), text records (avatar, description, url, social handles, AI agent metadata), content hash (IPFS/IPNS), ENSIP-25 agent-registration records, and ENSIP-26 agent context and endpoint discovery. Multiple records are batched into a single multicall transaction to save gas. Common text record keys: avatar, description, url, email, com.twitter, com.github, com.discord, ai.agent, ai.purpose, ai.capabilities, ai.category. ENSIP-25 support: Pass agentRegistration with registryAddress and agentId to automatically set the standardized agent-registration text record. This creates a verifiable on-chain binding between your ENS name and your agent identity in an ERC-8004 registry. ENSIP-26 support: Pass agentContext to set the agent-context text record (free-form agent description). Pass agentEndpoints with protocol URLs (mcp, a2a, oasf, web) to set agent-endpoint[protocol] discovery records. The returned transaction can be signed and submitted directly using any wallet framework (Coinbase AgentKit, ethers.js, etc.).

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