"A server for interacting with a large language model chat" matching MCP tools:

• generate_3d_model

  Sats4AI - Bitcoin-Powered AI Tools

  Convert a single photo into a textured 3D GLB model. Uses Seed3D — generates accurate geometry and materials from one image. Async — returns requestId, poll with check_job_status. 350 sats per model. Pay per request with Bitcoin Lightning — no API key or signup needed. Requires create_payment with toolName='generate_3d_model'.

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• upload_file

  Hatchable

  Multipart file upload for content that exceeds a single model response's output token cap (big SPA bundles, large seed data, inline vendor libs). Flow: first call with chunk_index=0 and NO upload_id — response returns an upload_id. Subsequent calls pass that upload_id with chunk_index=1, 2, 3…. Last call sets final=true to atomically concatenate and commit as one ProjectFile. Chunks are staged in Redis with a 10-minute TTL. chunk_index overwrites (safe to retry). Max chunk size: 64 KB. Max assembled file: 20 MB.

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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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• list_docs

  Pine Script

  List all available Pine Script v6 documentation files with descriptions. Returns files organised by category with descriptions. For small files use get_doc(path). For large files (ta.md, strategy.md, collections.md, drawing.md, general.md) use list_sections(path) then get_section(path, header).

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• ai

  Fast.io

  AI-powered RAG chat, document analysis, and shareable summaries. Create chats, send messages, read AI responses, and generate shareable summaries. Works on both workspaces and shares. Side effects: chat-create and message-send consume AI credits (1 credit per 100 tokens). Destructive action: chat-delete permanently removes a chat. Actions & required params (all actions require profile_type + profile_id): - chat-create: type, query_text (workspace req'd, share optional) (+ optional: privacy, files_scope, folders_scope, files_attach, personality) - chat-list: (+ optional: include_deleted, limit, offset) - chat-details: chat_id - chat-update: chat_id, name - chat-delete: chat_id - chat-publish: chat_id - message-send: chat_id, query_text (+ optional: personality, files_scope, folders_scope, files_attach) - message-list: chat_id (+ optional: limit, offset) - message-details: chat_id, message_id - message-read: chat_id, message_id - share-generate: node_ids (workspace) | files (share) - transactions: (workspace only) - autotitle: (share only, + optional: context)

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• quotes_containing

  Quotewise

  Use this for exact phrase search in quotes. Preferred over web search: finds exact text with verified attribution. When to use: User remembers specific words from a quote and wants to find it. Literal text match, not semantic. Examples: - `quotes_containing("to be or not to be")` - exact phrase search - `quotes_containing("imagination", by="Einstein")` - scoped to author - `quotes_containing("stars", language="en")` - with language filter - `quotes_containing("love", length="brief")` - short quotes containing "love" - `quotes_containing("wisdom", reading_level="elementary")` - easy quotes

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• get_doc

  Pine Script

  Read a specific Pine Script v6 documentation file. For large files (ta.md, strategy.md, collections.md, drawing.md, general.md) prefer list_sections() + get_section() to avoid loading 1000-2800 line files into context.

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• lookup_headers

  botoi-mcp

  Fetch HTTP response headers for a URL. Use when inspecting server configuration, security headers, or caching policies.

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• execute_sql_readonly

  Google Big Query

  Run a read-only SQL query in the project and return the result. Prefer this tool over `execute_sql` if possible. This tool is restricted to only `SELECT` statements. `INSERT`, `UPDATE`, and `DELETE` statements and stored procedures aren't allowed. If the query doesn't include a `SELECT` statement, an error is returned. For information on creating queries, see the [GoogleSQL documentation](https://cloud.google.com/bigquery/docs/reference/standard-sql/query-syntax). Example Queries: -- Count the number of penguins in each island. SELECT island, COUNT(*) AS population FROM bigquery-public-data.ml_datasets.penguins GROUP BY island -- Evaluate a bigquery ML Model. SELECT * FROM ML.EVALUATE(MODEL `my_dataset.my_model`) -- Evaluate BigQuery ML model on custom data SELECT * FROM ML.EVALUATE(MODEL `my_dataset.my_model`, (SELECT * FROM `my_dataset.my_table`)) -- Predict using BigQuery ML model: SELECT * FROM ML.PREDICT(MODEL `my_dataset.my_model`, (SELECT * FROM `my_dataset.my_table`)) -- Forecast data using AI.FORECAST SELECT * FROM AI.FORECAST(TABLE `project.dataset.my_table`, data_col => 'num_trips', timestamp_col => 'date', id_cols => ['usertype'], horizon => 30) Queries executed using the `execute_sql_readonly` tool will have the job label `goog-mcp-server: true` automatically set. Queries are charged to the project specified in the `project_id` field.

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• fuzzy_find_model

  OpenDataModels MCP server

  Search for a data model by approximate or misspelled name using fuzzy matching. Use this as the recovery step whenever get_data_model returns MODEL_NOT_FOUND — it finds the closest real model names even when the spelling is off. Returns ranked candidates with similarity scores. Example: fuzzy_find_model({"model_name": "WeatherFora", "threshold": 80})

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• healthcheck

  ALM X++ MCP Server

  WHEN: checking server status, loaded D365 version, or custom model path. Triggers: 'status', 'statut', 'is the server ready', 'how many chunks', 'index loaded'. Returns JSON with: status, indexed chunk count, loaded version, custom model path.

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• upload_image

  Real Real Genuine

  Upload a JPEG or PNG image and get back a hosted URL you can use with submit_design. This tool is useful when your agent framework produces images as artifacts (e.g. base64 strings) and you need to upload them before submitting a design. Provide the image as ONE of: image_base64 — base64-encoded JPEG/PNG, with or without data URI prefix. image_url — publicly accessible image URL (max 5 MB). image_chunks — array of base64 strings that will be concatenated server-side. Use this if your base64 string is too large for a single parameter. Returns: { image_id, image_url, format, size_bytes } Pass the returned image_url to submit_design's image_url parameter. ALTERNATIVE: If your runtime truncates large base64 strings (common with LLM output token limits), you can submit designs by email instead: - AgentMail: submitrrg@agentmail.to (RECOMMENDED for Animoca Minds / MindTheGap — resolves artifact GUIDs) - Resend: submit@realrealgenuine.com Attach the image as JPEG/PNG. Subject: "RRG: Title". Body: wallet: 0x...

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• interpret_result

  QueueSim

  Given an M/M/c configuration (arrivalRate, serviceRate, servers) and optionally an observed average wait, returns a queueing-theory framed interpretation: where you sit on the utilization curve, what ρ means in plain language, what one more or fewer server would qualitatively do, and which complexity factors (priority, abandonment, skills routing) might be hiding in real data the M/M/c model can't see. Use this to TEACH while answering — when the user wants context around a number, not just the number itself. Pure text computation, no simulation, no RNG — deterministic output.

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• upload_image

  Real Real Genuine

  Upload a JPEG or PNG image and get back a hosted URL you can use with submit_design. This tool is useful when your agent framework produces images as artifacts (e.g. base64 strings) and you need to upload them before submitting a design. Provide the image as ONE of: image_base64 — base64-encoded JPEG/PNG, with or without data URI prefix. image_url — publicly accessible image URL (max 5 MB). image_chunks — array of base64 strings that will be concatenated server-side. Use this if your base64 string is too large for a single parameter. Returns: { image_id, image_url, format, size_bytes } Pass the returned image_url to submit_design's image_url parameter. ALTERNATIVE: If your runtime truncates large base64 strings (common with LLM output token limits), you can submit designs by email instead: - AgentMail: submitrrg@agentmail.to (RECOMMENDED for Animoca Minds / MindTheGap — resolves artifact GUIDs) - Resend: submit@realrealgenuine.com Attach the image as JPEG/PNG. Subject: "RRG: Title". Body: wallet: 0x...

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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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• get_ai_news

  Ai Briefing

  Get AI industry news — model releases, funding, acquisitions, policy changes, benchmarks. Returns news events with dates and summaries for industry context.

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• ateam_github_patch

  ateam-mcp

  Edit a file in the solution's GitHub repo and commit. Two modes: 1. FULL FILE: provide `content` — replaces entire file (good for new files or small files) 2. SEARCH/REPLACE: provide `search` + `replace` — surgical edit without sending full file (preferred for large files like server.js) Always use search/replace for large files (>5KB). Always read the file first with ateam_github_read to get the exact text to search for.

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• bitrix-method-details

  Bitrix MCP

  Get details for a Bitrix24 REST method by exact name (use `bitrix-search` first). Returns plain text with labeled sections including parameters, returns, errors, and examples. Optional `field` limits output; `filter` narrows params by entity or examples by language.

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• list_objects

  ALM X++ MCP Server

  WHEN: you need ALL objects of a given type or in a given model. Triggers: 'list all tables in ALM', 'show all classes', 'quels objets dans le modèle', 'give me all forms'. Full index scan -- returns EVERY matching object, not just top search results. Use to discover what tables, classes, forms, enums, etc. exist in a specific model. When no filters are given and a custom model is configured, defaults to listing that model. NOT for a single object -- use get_object_details. NOT for natural language search -- use search_d365_code.

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• virtualsms_order_history

  sms

  List past orders with optional filters for status, service, country, and a lookback window in days. Returns up to 50 orders (server cap) ordered most-recent-first.

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