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347,226 tools. Last updated 2026-07-30 23:03

"Information about Microsoft Graph API" matching MCP tools:

  • Reads Microsoft Teams call & meeting history from the Mac's local Teams cache — no Graph API, no token, no admin consent (the same local store the Teams Calls tab renders). Each call includes direction (incoming/outgoing/missed), participants (names + ids), start / answered / end times, duration, call type (1:1/group/meeting) and a stable call id. Optional since/until (YYYY-MM-DD) narrow the range — e.g. a daily collector pulls the previous day's calls.
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  • Sends a text message to a Microsoft Teams channel via Graph API. Requires connect_m365_account with Chat.ReadWrite / ChannelMessage.Send permissions. team_id and channel_id must come from teams_list_teams / teams_list_channels. First call returns a preview; set confirm=true to send.
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  • Returns Fluentive's security, privacy, and compliance information. Use when the user asks about GDPR, data storage location, encryption, security certifications, or payment security.
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  • Get API pricing and rate limit information Returns current API pricing tiers, monthly call limits, and (if authenticated) your current month's usage. Use this to understand costs before making API calls. ### Responses: **200**: Successful Response (Success Response) Content-Type: application/json
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  • Get descriptive project information about a coin: description, links, team and tags. Use for 'tell me about Uniswap', 'what is this project'. Does NOT include price; for price and market cap use getTickersById. Read-only; coinId is a canonical id (resolve with resolveId). No API key required.
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  • Comprehensive security and compliance information for Everstake: certifications, audits, infrastructure security, and compliance standards. Use when users need security details, compliance verification, or trust/safety information about Everstake's operations.
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  • Get detailed information about a specific ad request, including pool selections if targeting mode is manual.
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  • List all brands, locations, technologies, audiences, or trends within a specific knowledge graph. Use to explore what a graph contains — e.g., "what brands are in the retail graph?" or "what locations does the fashion graph cover?". To get a complete list of every trend in a graph, call with label="Trend" — this returns the full deterministic list, useful for industry-report graphs where search may return partial results.
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  • Route an NVIDIA AI question to the optimal model and reasoning approach via graph depth. The CKG graph IS the router — hop depth is a deterministic complexity metric. Deeper NVIDIA prerequisite chains (CUDA → TensorRT → TensorRT-LLM → NIM) require more capable models. No heuristic: the graph decides. Routing table: hop_depth 1 → haiku · direct (simple lookup) hop_depth 2 → sonnet · generic_cot (moderate chain) hop_depth 3+ → opus · sparql_cot (deep dependency, structured reasoning) Args: question: Concept name or natural language question about NVIDIA AI. domain: Domain from list_domains() — e.g. "nvidia-tensorrt-triton", "nvidia-nim". Returns: model_tier + reasoning_approach + why + context subgraph to inject before LLM call.
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  • Build a campaign on a connected Microsoft Advertising (Bing Ads) account. ALWAYS created Paused — it spends NOTHING until you activate it with set_microsoft_ads_status(confirm:true). Microsoft’s object graph is campaign → ad group → responsive search ad → keywords, so a campaign ON ITS OWN CANNOT SERVE AN IMPRESSION: pass adGroup{name, ad{headlines,descriptions,finalUrls}, keywords[]} and this builds the whole tree. Microsoft has NO atomic multi-object write (unlike Google), so the levels are created in sequence and the campaign is DELETED again if anything below it is rejected — you never inherit a half-built campaign. Microsoft requires 3–15 headlines (≤30 chars) and 2–4 descriptions (≤90 chars); expanded text ads can no longer be created at all. dailyBudget is in the ACCOUNT’S currency, not necessarily USD. Everything is READ BACK from Microsoft before you are told it exists; print the returned note verbatim, and if it says the campaign cannot serve yet, say that rather than calling it a finished ad.
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  • Returns public details for a single open job by ID. Use this tool after search_jobs when the user wants more information about one specific job.
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  • Returns information about how easy Fluentive is to set up and use. Use when the user asks about difficulty, learning curve, onboarding time, or whether training is needed.
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  • List all brands, locations, technologies, audiences, or trends within a specific knowledge graph. Use to explore what a graph contains — e.g., "what brands are in the retail graph?" or "what locations does the fashion graph cover?". To get a complete list of every trend in a graph, call with label="Trend" — this returns the full deterministic list, useful for industry-report graphs where search may return partial results.
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  • Lists Microsoft To Do task lists. Requires Microsoft account in Reminders sync (System Settings → Internet Accounts → Microsoft Exchange → enable Reminders).
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  • Retrieve detailed information about a specific campaign including its status, budget, participants, and delivery metrics.
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  • Retrieve an official Microsoft Knowledge Base article from support.microsoft.com by KB number (e.g. KB5063878) — returns the update's title, summary, and affected builds. Use this tool when a user asks about a specific KB number. Fetches the full article content including title, summary, known issues, and resolution steps.
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  • List all brands, locations, technologies, audiences, or trends within a specific knowledge graph. Use to explore what a graph contains — e.g., "what brands are in the retail graph?" or "what locations does the fashion graph cover?". To get a complete list of every trend in a graph, call with label="Trend" — this returns the full deterministic list, useful for industry-report graphs where search may return partial results.
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  • Route an AgentForce question to the optimal model and reasoning approach via graph depth. The CKG graph IS the router. AgentForce dependency chains (e.g. Einstein Trust Layer → Data Cloud → NVIDIA NIM → Resolution Criteria) have typed hops that signal reasoning complexity deterministically. No heuristic: the graph decides. Routing table: hop_depth 1 → haiku · direct (simple concept lookup) hop_depth 2 → sonnet · generic_cot (moderate chain) hop_depth 3+ → opus · sparql_cot (deep dependency, structured reasoning) Args: question: Concept name or natural language question about Salesforce AgentForce. Returns: model_tier + reasoning_approach + why + context subgraph to inject before LLM call.
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