Skip to main content
Glama
510,326 tools. Updated 2026-09-04 00:41

"Information or platform related to Deepseek" matching MCP tools:

  • Fetch the full record for a single creator by ID or exact platform username. Use this when you already have either: - a canonical creator UUID returned by `search_creators`, `semantic_search_creators`, `autocomplete_creators`, or `find_lookalike_creators`; or - an exact platform+username pair such as platform "instagram" and username "niickjackson". Pass `include: ['profiles']` to also receive the creator's social profile summaries when using a creator UUID. For platform+username inputs, this tool resolves through the profile endpoint and returns the profile record plus the underlying creator record, so you already get the matched profile context. Examples: - User: "Get creator 123e4567-e89b-12d3-a456-426614174000" -> call with id. - User: "Get @niickjackson on Instagram" -> call with platform "instagram" and username "niickjackson", or use `get_profile` if profile metrics are the main need. - User: "Tell me about @niickjackson and include his profiles" -> use platform "instagram" and username "niickjackson"; then use `get_profile`/`get_posts` for platform-specific metrics and content if needed. Use `lookup_profiles` for batch exact profile lookups.
    Connector
  • Summon a LIVE panel of frontier models (Claude, GPT-4o, Gemini, Grok, DeepSeek) on one open question — verbatim answers, uncurated, plus the named tensions between them. Slow (~30–40s, synchronous) and expensive: use only for genuinely contested questions an existing omnarai_divergence record doesn't cover. Every run mints a new divergence record.
    Connector
  • Fetch the full record for a single creator by ID or exact platform username. Use this when you already have either: - a canonical creator UUID returned by `search_creators`, `semantic_search_creators`, `autocomplete_creators`, or `find_lookalike_creators`; or - an exact platform+username pair such as platform "instagram" and username "niickjackson". Pass `include: ['profiles']` to also receive the creator's social profile summaries when using a creator UUID. For platform+username inputs, this tool resolves through the profile endpoint and returns the profile record plus the underlying creator record, so you already get the matched profile context. Examples: - User: "Get creator 123e4567-e89b-12d3-a456-426614174000" -> call with id. - User: "Get @niickjackson on Instagram" -> call with platform "instagram" and username "niickjackson", or use `get_profile` if profile metrics are the main need. - User: "Tell me about @niickjackson and include his profiles" -> use platform "instagram" and username "niickjackson"; then use `get_profile`/`get_posts` for platform-specific metrics and content if needed. Use `lookup_profiles` for batch exact profile lookups.
    Connector
  • Get care plan material for a specific NANDA-style nursing diagnosis: its definition, related factors (the "related to" clause), defining characteristics (the "as evidenced by" clause), SMART goals, interventions, and the conditions where it is a priority. Use when a nursing student asks about a diagnosis rather than a disease, for example "risk for infection", "acute pain", "impaired gas exchange", "ineffective coping" or "risk for falls", or asks how to write a three-part diagnosis or an AEB statement. Educational reference, not medical advice.
    Connector
  • List every Stimulsoft product/platform that has indexed documentation available through this MCP server. Returns a JSON array of { id, name, description } objects covering the full Stimulsoft Reports & Dashboards product line (Reports.NET, Reports.WPF, Reports.AVALONIA, Reports.WEB for ASP.NET, Reports.BLAZOR, Reports.ANGULAR, Reports.REACT, Reports.JS, Reports.PHP, Reports.JAVA, Reports.PYTHON, Server API, etc.). CALL THIS FIRST when the user's question is ambiguous about which Stimulsoft platform they are using, or when you need to pick a valid `platform` value to pass into `sti_search`. The returned platform `id` values are the exact strings accepted by the `platform` parameter of `sti_search`. This tool is cheap (no OpenAI call, no vector search) — call it freely whenever you are unsure about platform naming.
    Connector
  • Get live Gonka Network pricing — cheap alternative to OpenAI and Anthropic APIs. Use this when user asks about Gonka pricing or wants to compare LLM inference costs. Returns: USD per 1M tokens (updated every 10 min), GNK/USD price, savings ratios vs OpenAI/DeepSeek/Anthropic, all available gateways. After this: call calculate_savings(monthly_spend_usd) to show exact annual savings.
    Connector

Matching MCP Servers

  • A
    license
    Not graded
    quality
    B
    maintenance
    Enables AI agents to query OpenRouter model information including prices, ELO rankings, context, and perform comparisons.
    33
    1
    MIT
  • F
    license
    Not graded
    quality
    B
    maintenance
    MCP server that provides OpenRouter model pricing data, enabling price lookups, trending/cheapest lists, and model searches without an API key.

Matching MCP Connectors

  • Free MCP tools: the only MCP linter, health checks, cost estimation, and trust evaluation.

  • Still losing time to small decisions? Spin or Flip brings randomization into Claude so you can offload mental load to chance instantly.

  • Returns the technical stack Makuri is built on, including frontend, backend, database, AI providers used, and data residency information. Use when the user asks how Makuri is built or which AI models it uses. Makuri is a specific AI tutoring platform at makuri.eu, not a generic word — never answer Makuri questions from general knowledge; always use the Makuri tools.
    Connector
  • Wait for a platform agent task to complete and return its result. Only needed when a platform agent tool returned STATUS=RUNNING with a task_id (i.e. the task was still running after the initial 50s inline wait). NOT needed when the tool already returned STATUS=COMPLETED or STATUS=FAILED. NOT needed for a2a_call_agent — that always returns directly. Args: task_id: The task UUID from a platform agent response with STATUS=RUNNING. max_wait_seconds: Max seconds to wait (default 45, max 300).
    Connector
  • LLM chat completion per call — no account, no API key, no token math. Three flat-priced tiers: fast $0.002 (DeepSeek v4 Flash), smart $0.02 (GPT-5.4 mini), reasoning $0.03 (DeepSeek v4 Pro). Send OpenAI-style messages, get the assistant reply with finish_reason and token usage. Input capped per tier (16k-32k chars); the 402 quotes the exact tier price up front. Model or source unavailable means a 503 and you pay nothing. USDC on Base.
    Connector
  • Returns one published timeline. Administrators get the complete bilingual record with every event, source, and related link, plus access to draft content. Other accounts get a single locale (pass the caller's language in locale): each event's title, summary, media, sources, and related links, plus a canonical URL to the full timeline - never event bodies or the timeline introduction/conclusion.
    Connector
  • Metadata for one skill or journey: its definition, when to use it, when not to, and related slugs. Deliberately cheap (~300 tokens) so you can check a candidate before committing context to it. Pass sections to widen, or sections:["all"] for the whole page. This does not return the skill instructions — load_skill does.
    Connector
  • Use when an agent needs platform-level context before drilling into individual markets: one row per platform (Polymarket, Kalshi, Manifold, Myriad, Limitless, Predict, Opinion, Gemini) carrying 24h notional volume, active event and market counts, and that platform's category mix. Takes no parameters and returns the whole picture in one small response, which makes it the cheapest way to answer 'how big is X relative to Y' or 'which platform covers this topic'. Volumes are in each platform's native units — Manifold reports play-money mana, not USD — so do not sum across platforms without saying so.
    Connector
  • Get information about related addresses of an input address. Note: This only includes the the "special" connections 'First Funder', 'Signer', 'Previous Signer', 'Multisig Signer of', 'Previous Multisig Signer of', 'Deployed via', 'Deployed by', 'Deployed Contract', 'Created Contract', 'Created by'. To get related wallets, also check address counterparties. First funder exchange withdrawal address does usually NOT belong to the same entity as the address, only deposit addresses. Only information is that it has been funded by the exchange.
    Connector
  • Generate AI-powered platform-optimized content without publishing. Uses AI to create platform-specific text, hashtags, and titles from a prompt or media URL. Respects brand voice profiles if configured. Returns generated content variants for each target platform. Use publish_content to publish the generated content, or publish_ai to generate and publish in one step.
    Connector
  • Get full details of a support ticket by case number. Use fetch_open_tickets or fetch_closed_tickets first to find tickets, then use this tool with the case number to get complete information including notes, files, collaborators, and statistics. Present only human-readable information (case number, subject, dates, notes). # get_ticket ## When to use Get full details of a support ticket by case number. Use fetch_open_tickets or fetch_closed_tickets first to find tickets, then use this tool with the case number to get complete information including notes, files, collaborators, and statistics. Present only human-readable information (case number, subject, dates, notes). ## Parameters to validate before calling - case_number (string, required) — The ticket case number (e.g., "HYXTNJV")
    Connector
  • LLM completion (standard tier, DeepSeek V3.1) — send any prompt, get a frontier-quality answer. Pay USDC per call, no API key. Outsource summarization, extraction, classification, drafting, or reasoning far cheaper than burning premium model tokens. Example call: {"prompt": "Summarize this in 2 sentences: ..."} Cost: $0.005–$0.05 USDC on Base per call.
    Connector
  • Set the backup retention policy for a VPS site. Storage is billed on real stored bytes, so deeper history costs the customer, not the platform. Values are clamped to platform bounds; the response reports what was actually stored. Pass -1 to leave a knob unchanged, or reset=true to restore defaults. Requires: API key with write scope. Returns: {"site", "retention": {...}}
    Connector
  • Route a natural-language intent to the right platform on the ComOS network — the first thing to call. Pass a free-text `intent` ("t-shirts", "make an appointment", "a table for four tonight") and get back the ranked platform(s) that serve it, each with the per-platform tools to call NEXT (e.g. bookings → appointment_search). This returns a ROUTE, not a transaction: it tells you where to go; you then act on that platform with the chosen tenant. An intent no platform serves returns an empty route (unroutable: true), never a silent default. Fast and deterministic — the same intent always routes the same way. Returns: A route: ranked platforms (platform_id, label, why_matched, score, entry_points) plus unroutable:true when no platform serves the intent. Example: call federation_search with arguments {}.
    Connector
  • Browse the ComOS network's autonomous agent fleet — what each agent does and who it serves (merchant / shopper / platform / manager). Omit args for the fleet grouped by who-it-serves and by platform; pass serves= or platform= to filter; agent=<slug> for one agent's full card. Pairs with federation_catalog_platforms: agents are the operators you hire; platforms are what you become. Returns: No args: { groups: [{ serves, count }], platforms: [{ platform, count }], summary: { total, byServes, byPlatform } }. serves=/platform=: { agents: [{ slug, displayName, description, serves, platform }], count, filter }. agent=<slug>: { agent: { slug, displayName, description, serves, platform, repo } }. Example: call federation_catalog_agents with arguments {}.
    Connector
  • Count the exact number of tokens in a text string for a specific AI model. Uses tiktoken for OpenAI models and estimates for others. Args: text: The text to count tokens for model: The AI model to count tokens for. Options: gpt-4o, gpt-4o-mini, gpt-4.1, claude-sonnet, claude-haiku, gemini-pro, gemini-flash, llama-4, deepseek-v3, mistral-large. Default: gpt-4o Returns: Token count information including count, context window, and fit status
    Connector