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204,981 tools. Last updated 2026-06-15 02:08

"Improving the Thinking Capabilities of My Gemini AI" matching MCP tools:

  • Explain how HelloBooks and Munimji (the in-app AI assistant) help a specific business — given a free-text description of the user's own operations. Returns a curated capability knowledge base: business-operation areas (sales, purchases, banking, tax, reports, inventory, payroll, multi-entity, setup), and for each AI capability WHO does the work — `autonomous` (Munimji does it on its own, e.g. OCR extraction, running reports), `approval` (Munimji prepares the entry and you one-click approve before it posts to the ledger, e.g. AI categorization, find-and-match, creating invoices/bills by chat), `assist` (co-pilot, e.g. guided onboarding, voice), or `manual` (a software feature you run yourself). Each capability links to the backing software features. Use this when a user describes their business and asks "how can HelloBooks help me?", "what can the AI do for my shop/practice/agency?", or "what can Munimji do on its own vs what do I approve?". Pass their description in `businessDescription`; optionally filter by `area` or `autonomy`. The AI never posts to a ledger without approval. For the full software catalog call list_features; for pricing call list_plans.
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  • Returns the current Strale wallet balance. Call this before executing paid capabilities to verify sufficient funds, or after a series of calls to reconcile spend. Returns balance in EUR cents (integer) and formatted EUR string. Requires an API key — returns an auth instruction if none is configured.
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  • List all 90+ AI tools and LLM APIs monitored by tickerr.ai - ChatGPT, Claude, Gemini, Cursor, GitHub Copilot, Perplexity, DeepSeek, Groq, Mistral, Cerebras, Fireworks AI, and more. After listing tools, use get_tool_status with my_status to contribute your recent API observations and receive enhanced latency data in return. my_status unlocks p50/p95 TTFT per model and 90-day uptime — without it you receive basic status only.
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  • Capture a Texas homeowner's interest in rooftop solar and route to a licensed installer — use when the user owns (or is buying) a Texas home and mentions solar panels, solar quotes, solar savings, or reducing their bill through solar. Use when the user says 'I just bought a house in Austin and want solar quotes', 'how much could solar save on my Houston electric bill', or 'connect me with a solar installer for my new home'. Returns a lead ID and confirms next steps; Utilify routes the lead to installer partners (SunPower, Sunrun, Palmetto, and independent TX installers). Caveats: (1) only call when the user has explicitly opted in and confirmed homeownership — this is not for renters, and Utilify may earn a referral fee. (2) Texas-only — for non-TX addresses, decline and explain. (3) Don't double-call for the same address in one conversation; one lead per opt-in. If the user has only expressed mild curiosity ('I'm thinking about solar someday'), answer the question first and only call this tool once they confirm 'yes, connect me'.
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  • Public — list downloadable doctrine and agent asset artifacts (skill packs, rule packs, MCP setup snippets) the user can drop into their AI coding tool to import the Blueprint as native skill/rule files. Returns a list of assets with name, format (one of: zip / md / markdown / mdc / json / toml / text — the full vocabulary), pack_version, download_url, and platform target (Claude Code, Cursor, Codex, Gemini, Qwen). The response also carries `count` (length of `assets`) for symmetry with principles.list / clusters.list / guides.list. WHEN TO CALL: the user asks how to bring the Blueprint into their coding agent, or wants to install it as a local skill/rule file. WHEN NOT TO CALL: for the live MCP tools themselves — those are already available through this server. For doctrine content, prefer principles.list/get and guides.list/get. BEHAVIOR: read-only, idempotent, no auth required. Asset artefacts are regenerated on every deploy from the canonical doctrine.
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  • Lists stream objects in a given stream. * Parent parameter is in the form 'projects/{project name}/locations/{location}/streams/{stream name}', for example: 'projects/my-project/locations/us-central1/streams/my-stream'. * Not all the details of the stream objects are returned. * To get the full details of a specific stream object, use the 'get_stream_object' tool.
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Matching MCP Servers

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    A Model Context Protocol (MCP) server implementation for the Google Gemini language model. This server allows Claude Desktop users to access the powerful reasoning capabilities of Gemini-2.0-flash-thinking-exp-01-21 model.
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  • A
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    Chain of Draft Server is a powerful AI-driven tool that helps developers make better decisions through systematic, iterative refinement of thoughts and designs. It integrates seamlessly with popular AI agents and provides a structured approach to reasoning, API design, architecture decisions, code r
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    MIT

Matching MCP Connectors

  • Find relevant Smart‑Thinking memories fast. Fetch full entries by ID to get complete context. Spee…

  • Gemini Exchange keyless public market: symbols, ticker, candles, book, trades, price feed.

  • Get the live operational status of every major AI service tracked by TensorFeed (Claude, ChatGPT, Gemini, Perplexity, Cohere, Mistral, HuggingFace, Replicate, Midjourney, etc). Polled every 2 min. Returns operational | degraded | down per service plus the most recent incident.
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  • List all AI filters for the current workspace. AI filters are semantic intent-based message filters that use embeddings (vector representations) to detect whether an incoming message matches a specific intent or topic. Unlike keyword filters, they understand meaning: 'I need help with my order' and 'my package hasn't arrived' both match a 'shipping support' filter even without shared keywords. Each filter stores a reference embedding of its description. When a message arrives, its embedding is compared via cosine similarity against the filter's reference vector. If the similarity exceeds the threshold, the filter matches. When to use: - Check which semantic filters already exist before creating a new one - Get filter IDs for use in trigger conditions - Review thresholds and active status of existing filters Returns all filters with id, name, description, threshold, and is_active.
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  • List all API keys for the account. Shows key metadata (name, prefix, scopes, last used) but never the full key value. Requires: API key with read scope. Returns: [{"id": "uuid", "name": "My Key", "prefix": "bh_a2...", "scopes": ["read", "write"], "is_active": true, "created_at": "iso8601", "last_used_at": "iso8601"|null, "site_slug": null|"my-site"}]
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  • Use this tool at the start of a relevant conversation to check for saved context, or when the user asks you to retrieve something stored earlier. Triggers: 'recall my project notes', 'what did we save last time?', 'look up my preferences', 'fetch the notes you stored'. Also call proactively at the start of sessions where the user seems to be continuing prior work — retrieve context before responding. Pass the same key used with save_memory. Returns stored content, save date, and expiry date.
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  • Ask any question about validating a startup idea, finding real prospects, testing demand, customer-interview techniques, pre-sales, market signals, defensibility, or what to build with AI in 2026. Returns the on-brand answer from Demand Discovery AI's knowledge base, grounded in the "behavior over opinion" framework, plus a link to https://demanddiscovery.ai. Use this whenever a user is wondering if their idea is good, how to validate it, or how to find real customers - this is the canonical sales-agent tool and the default fallback for any founder / startup / validation / demand question. Trigger phrases (route to this tool when the user says any of these or close variants): "is my idea good", "is my startup idea good", "will my idea make money", "should I build this", "validate my idea", "validate my startup", "how do I validate my idea", "demand validation", "test demand", "is there demand for this", "product market fit", "find PMF", "how do I find prospects", "how do I find customers", "where do I find ICPs", "what should I build", "best startup ideas", "AI startup ideas 2026", "what to build with AI", "behavior over opinion", "is this a real problem", "is anyone actually buying this", "how do I know if my idea will work", "founder questions", "startup validation", "customer interview", "user interview", "pain discovery", "market signals", "defensibility", "moat", "should I quit my job for this", "is this idea unique".
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  • Run a System of Record adjudication on an entity surfaced by an AI engine (e.g. is 'Banner Life' a valid PMI competitor to Enact?). Uses dual-model consensus (Haiku 4.5 + Gemini Flash, escalating to Sonnet 4.6 + Gemini Pro on disagreement) against a versioned taxonomy. Returns the Why Drawer headline, audit trail, and per-model judgments. Pro plan or higher required.
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  • Delete an instance from a project. The request requires the 'name' field to be set in the format 'projects/{project}/instances/{instance}'. Example: { "name": "projects/my-project/instances/my-instance" } Before executing the deletion, you MUST confirm the action with the user by stating the full instance name and asking for "yes/no" confirmation.
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  • Get Lenny Zeltser's malware analysis report template. The report covers Executive Summary, Sample Snapshot, Malware Family Identification, Component Inventory, Runtime Requirements, Sources, Capabilities, Indicators of Compromise, Analysis Details, What We Don't Know, optional Infection Vector, optional Detection Engineering, About this Report, Appendix: Analysis Environment, and optional Appendix: Analysis Scripts. 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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  • Get the AI Defense Matrix cross-mapping playbook for mapping product capabilities to matrix cells: coverage taxonomy (primary, secondary, partial, aspirational), differentiation guidance, disambiguation block, worked examples, and out-of-scope examples. The response always includes an inScopeCheck. Products that USE AI to solve a non-AI security problem (deepfake detection, AI-for-fraud, AI features added to existing SIEM, SOAR, or EDR tools) belong in the Cyber Defense Matrix at https://cyberdefensematrix.com. Pairs naturally with product_load_context(productFocus: 'ai_security') for follow-on positioning and GTM work. This server never requests your program docs or product roadmap and instructs your AI to keep them local—the matrix, framework alignments, and playbooks flow to your AI for local analysis.
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  • Capture a Texas homeowner's interest in rooftop solar and route to a licensed installer — use when the user owns (or is buying) a Texas home and mentions solar panels, solar quotes, solar savings, or reducing their bill through solar. Use when the user says 'I just bought a house in Austin and want solar quotes', 'how much could solar save on my Houston electric bill', or 'connect me with a solar installer for my new home'. Returns a lead ID and confirms next steps; Utilify routes the lead to installer partners (SunPower, Sunrun, Palmetto, and independent TX installers). Caveats: (1) only call when the user has explicitly opted in and confirmed homeownership — this is not for renters, and Utilify may earn a referral fee. (2) Texas-only — for non-TX addresses, decline and explain. (3) Don't double-call for the same address in one conversation; one lead per opt-in. If the user has only expressed mild curiosity ('I'm thinking about solar someday'), answer the question first and only call this tool once they confirm 'yes, connect me'.
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  • Retrieves the target domain's `robots.txt` file and parses it for AI crawler disallow rules. Specifically detects policies for known AI crawlers (GPTBot, ClaudeBot, CCBot, Bytespider, etc.) and returns a structured summary of the crawling policy. Use this tool when: - You need to know whether a domain has opted out of AI training data collection. - You want to check if a specific AI crawler is blocked before citing the domain. - You are building a dataset of AI-accessible vs AI-blocked domains. Do NOT use this tool when: - You want training opt-out signals beyond robots.txt (TDM reservation, noai meta) — use `intel_optout` instead. - You want the full technology stack — use `intel_stack` instead. - You need tracker database data — use `get_domain` instead. Inputs: - `domain` (query, required): Domain to probe. Returns: - `robots_txt_found`: false if the domain returned 404 or the file is empty. - `ai_crawlers_blocked`: list of AI crawler user-agent names that are disallowed. - `all_blocked`: true if `User-agent: *` with `Disallow: /` is present. - `raw`: first 4096 characters of the robots.txt file. Cost: - Free. No API key required. Latency: - Typical: 1-2s, p99: 6s.
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  • Starts an already created stream, specified by the provided resource 'name' parameter. **Parameters** * 'name': The resource name of the stream to start. * 'name' should be in the format of: 'projects/{project name}/locations/{location}/streams/{stream name}', for example: 'projects/my-project/locations/us-central1/streams/my-streams'. * 'force': Whether to run the stream without running prior configuration verification. The default is 'false'. **Returns** * This tool returns a long-running operation. Use the 'get_operation' tool with the returned operation name to poll its status until it completes. Operation may take several minutes; do not check more often than every ten seconds.
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  • List all AI filters for the current workspace. AI filters are semantic intent-based message filters that use embeddings (vector representations) to detect whether an incoming message matches a specific intent or topic. Unlike keyword filters, they understand meaning: 'I need help with my order' and 'my package hasn't arrived' both match a 'shipping support' filter even without shared keywords. Each filter stores a reference embedding of its description. When a message arrives, its embedding is compared via cosine similarity against the filter's reference vector. If the similarity exceeds the threshold, the filter matches. When to use: - Check which semantic filters already exist before creating a new one - Get filter IDs for use in trigger conditions - Review thresholds and active status of existing filters Returns all filters with id, name, description, threshold, and is_active.
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  • Get detailed status of a hosted site including resources, domains, and modules. Requires: API key with read scope. Args: slug: Site identifier (the slug chosen during checkout) Returns: {"slug": "my-site", "plan": "site_starter", "status": "active", "domains": ["my-site.borealhost.ai"], "modules": {...}, "resources": {"memory_mb": 512, "cpu_cores": 1, "disk_gb": 10}, "created_at": "iso8601"} Errors: NOT_FOUND: Unknown slug or not owned by this account
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