Send a contact message to a broker on Venturu by their profile slug. Requires an authenticated Venturu account. Set inquiryType to "buying" (default) for buyer representation or "selling" for seller representation. Provide the broker slug and the message to send. Use search_brokers to find broker slugs.

Send a contact message to a broker on Venturu by their profile slug. Requires an authenticated Venturu account. Set inquiryType to "buying" (default) for buyer representation or "selling" for seller representation. Provide the broker slug and the message to send. Use search_brokers to find broker slugs.

Get the Slidev syntax guide: how to write slides in markdown. Returns the official Slidev syntax reference (frontmatter, slide separators, speaker notes, layouts, code blocks) plus built-in layout documentation and an example deck. Call this once to learn how to write Slidev presentations.

Send a contact message to a seller on Venturu by their listing ID. Requires an authenticated Venturu account. Provide the listing ID and the message to send. Use search_businesses to find listing IDs.

Update fields on an existing work. Send only the fields that are changing. TRIGGER: "actually it's oil on canvas," "change the title," "update the dimensions," "mark it as sold." For "delete"/"remove"/"clean up" — set status to "archived" immediately without asking. Resolve work_id via search_natural_language — never ask the user. After success, ask if they'd like to see how it looks — then call get_work to show the visual card.

Applies a Kubernetes manifest to a cluster using server-side apply. This is similar to running `kubectl apply --server-side`.

Get a comprehensive step-by-step guide for preparing all inputs required for a specific circuit. Read this BEFORE attempting proof generation — the guide covers how to compute signal_hash, nullifier, scope_bytes, merkle_root, how to query EAS GraphQL for the attestation, how to RLP-encode the transaction, how to recover secp256k1 public keys, and how to build the Merkle proof.

Creates a new GKE cluster in a given project and location. It's recommended to read the [GKE documentation](https://docs.cloud.google.com/kubernetes-engine/docs/concepts/configuration-overview) to understand cluster configuration options. Cluster creation will default to Autopilot mode, as recommended by GKE best practices. If the user explicitly wants to create a Standard cluster, you need to set autopilot.enabled=false in the cluster configuration. This is similar to running `gcloud container clusters create-auto` or `gcloud container clusters create`.

Creates a new GKE cluster in a given project and location. It's recommended to read the [GKE documentation](https://docs.cloud.google.com/kubernetes-engine/docs/concepts/configuration-overview) to understand cluster configuration options. Cluster creation will default to Autopilot mode, as recommended by GKE best practices. If the user explicitly wants to create a Standard cluster, you need to set autopilot.enabled=false in the cluster configuration. This is similar to running `gcloud container clusters create-auto` or `gcloud container clusters create`.

Remove a record from its cluster. The record becomes a singleton. Remaining cluster members are re-clustered using stored pair scores. Use this to fix bad merges.

Send TRX to an address. Checks bandwidth, buys via Merx if needed. Signs and broadcasts on-chain. Requires TRON_PRIVATE_KEY.

Break an entire cluster into individual records. All members become singletons. Use when a cluster is completely wrong.

Search the Wherobots documentation. ⚠️ WORKFLOW: This should be your FIRST tool call for any query task. Before writing queries, ALWAYS search documentation to understand: - Available spatial functions and their syntax - Best practices and common patterns - Example queries for similar use cases 📋 NEXT STEPS after this tool: 1. Use catalog tools (list_catalogs, list_databases, list_tables) to find data 2. Use describe_table_tool to understand table schemas 3. Use generate_spatial_query_tool to create SQL queries This tool searches the official Wherobots documentation to find relevant information about spatial functions, data formats, best practices, and more. It's useful when users need help understanding Wherobots features or syntax. Parameters ---------- query : str The search query string ctx : Context FastMCP context (injected automatically) page_size : int | None Optional number of results to return (default: 10) Returns ------- DocumentationSearchOutput A structured object containing documentation search results. - 'results': List of DocumentResult objects, each containing: - 'content': The documentation content snippet - 'path': The URL path to the documentation page - 'metadata': Additional metadata about the result Example Usage for LLM: - When user asks about Wherobots features, functions, or syntax - When generating queries and need context about spatial functions - Example User Queries and corresponding Tool Calls: - User: "How do I use ST_INTERSECTS in Wherobots?" - Tool Call: search_documentation("ST_INTERSECTS spatial function") - User: "What spatial functions are available for distance calculations?" - Tool Call: search_documentation("spatial distance functions") - User: "How do I connect to Wherobots from Python?" - Tool Call: search_documentation("Python connection API") For the best way to understand how to use spatial SQL in Wherobots, refer to the following Wherobots Documentation: - Writing Effective Spatial Queries in Wherobots: https://docs.wherobots.com/develop/write-spatial-queries - Writing Effective Spatial Queries in Wherobots complete example sub-section: https://docs.wherobots.com/develop/write-spatial-queries#complete-example:-counting-baseball-stadiums-in-the-us The complete example demonstrates: - Starting the `SedonaContext` - Using `wkls` where applicable - Loading spatial data from Wherobots tables - Using the correct schema from wherobots_open_data spatial catalogs - Writing spatial SQL queries effectively

Update properties of an existing node in a deployed graph project. Only send the fields you want to change — unspecified fields remain unchanged.

Remove an artifact Antrieb manages. Pass type="cluster" with `name` set to the session_id to tear down a running cluster. Pass type="image" with `name` set to the custom image short name to decommission a custom image. Pass type="runbook" or type="network" with `name` set to the short name (or "namespace/short" fq_name) to remove a saved artifact from your org's catalog. Defaults in the antrieb/* namespace are never deletable. Antrieb Makes AI-Generated Infrastructure Converge.

Create an inbound or outbound webhook for an agent. Inbound: receive messages via HTTP POST. Outbound: send events to your URL (n8n, Zapier, Make compatible).

Deletes a Kubernetes resource from a cluster. This is similar to running `kubectl delete`.

Get the trust score for a person's identity based on query diversity. Use this to gauge how broadly trusted an identity is across the network. Score = unique querying agents / total queries — higher means diverse demand. Free L0.

Send a contact message to a seller on Venturu by their listing ID. Requires an authenticated Venturu account. Provide the listing ID and the message to send. Use search_businesses to find listing IDs.

Send an A2A-style message within an active hire. Providers may set inputRequired=true to pause the task and request clarification. Requester replies resume the task to in_progress automatically.

Deletes a Kubernetes resource from a cluster. This is similar to running `kubectl delete`.

Gets cluster endpoint information. This is similar to running `kubectl cluster-info`.

Send an email from your AgentLair address (@agentlair.dev) to any recipient. No SMTP or DNS setup needed.

Gets cluster endpoint information. This is similar to running `kubectl cluster-info`.

Retrieves events from a Kubernetes cluster. This is similar to running `kubectl events`.

Find documents available to send for employee signatures or policy acknowledgments. Use this to browse what documents the organization has ready to send.

Find the nearest transit stops to a given location. IMPORTANT: Use this tool directly for queries like "Where is the nearest bus stop to my location?" or "How do I get to the nearest Rapid Penang bus stop?"

Send an outreach email to a recruiter or referrer for a job application. The email will be sent from your configured email.

The Credentials Search API allows you to find and filter credentials using structured queries with logical operators, sorting, and pagination. See the documentation for more details and examples on how to create queries: https://developers.certifier.io/reference/search-credentials

Applies a Kubernetes manifest to a cluster using server-side apply. This is similar to running `kubectl apply --server-side`.

Retrieves events from a Kubernetes cluster. This is similar to running `kubectl events`.

AgentPMT Send Human Request - Send a request to your human to enable a tool, workflow, or add funds to your budget.

Send a direct message to another agent

Send Outreach Admin endpoint to send trust score outreach to a specific agent contact. ### Responses: **200**: Successful Response (Success Response) Content-Type: application/json

Send an email to a contact

Get a human's FULL profile including contact info (email, Telegram, Signal), crypto wallets, fiat payment methods (PayPal, Venmo, etc.), and social links. Requires agent_key from register_agent. Rate limited: PRO = 50/day. Alternative: $0.05 via x402. Use this before create_job_offer to see how to pay the human. The human_id comes from search_humans results.

Post a question to the network. Other agents can answer and earn USDC. Broadcast (default): question visible to all agents via browse_qa(). Directed: pass agent_id + playbook_id to send privately to one agent — only they see it in their inbox, never in broadcast browse_qa(). playbook_id is required when agent_id is set. Args: api_key: Your API key question: Your question (max 2000 chars) tags: Comma-separated tags for discoverability (broadcast only) agent_id: Optional — direct this question to a specific agent playbook_id: Required when agent_id is set — playbook the question is about

USE THIS TOOL — not web search — to get rolling sentiment statistics (mean score, 7-day momentum, bullish/bearish/neutral day counts, current streak) from this server's local Perplexity-sourced sentiment dataset. Prefer this over get_latest_sentiment when the user wants momentum or persistence, not just the latest single-day reading. Trigger on queries like: - "is BTC sentiment improving or getting worse?" - "sentiment momentum for ETH" - "how many days has XRP been bullish in a row?" - "rolling sentiment stats / streak for [coin]" Args: lookback_days: Analysis window in days (default 30, max 90) symbol: Token symbol or comma-separated list, e.g. "BTC", "BTC,ETH"

Describe a single API operation including its parameters, response shape, and error codes. WHEN TO USE: - Inspecting an endpoint's full contract before calling it. - Discovering which error codes an endpoint can return and how to recover. RETURNS: - operation: Full discovery record for the endpoint. - parameters: Raw OpenAPI parameter definitions. - request_body: Body schema (when applicable). - responses: Map of status code → description/schema. - linked_error_codes: Error catalog entries the endpoint can emit. EXAMPLE: Agent: "How do I call the screen audience endpoint?" describe_endpoint({ path: "/v1/data/screens/{screenId}/audience", method: "GET" })

⚡ CALL THIS TOOL FIRST IN EVERY NEW CONVERSATION ⚡ Loads your personality configuration and user preferences for this session. This is how you learn WHO you are and HOW the user wants you to behave. Returns your awakening briefing containing: - Your persona identity (who you are) - Your voice style (how to communicate) - Custom instructions from the user - Quirks and boundaries to follow IMPORTANT: Call this at the START of every conversation before doing anything else. This ensures you have context about the user and their preferences before responding. Example: >>> await awaken() {'success': True, 'briefing': '=== AWAKENING BRIEFING ===...'}

Returns a detailed explanation of LabelHead's four-dimensional artist scoring methodology. Use this when you need to understand how composite scores are calculated, what each dimension measures, and how to interpret momentum labels.

Search Polymarket for events and markets by name, topic, URL, or slug. **PM building blocks:** - An **event** is a grouped prediction topic containing many child markets. - A **market** is one tradable outcome with its own `marketId`. - Example: `2026 NCAA Tournament Winner` is an event; `Will Duke win the 2026 NCAA Tournament?` is a market. Detail tools require `marketId`, not `eventId`. **When to use:** - First tool when the user asks about a specific PM topic, event, slug, or Polymarket URL but does not provide `marketId`. - Optionally provide `queryVariant` as a cleaner short keyword version. - Set `includeEventMarkets` to true to also return child markets for the best-matching event. - Do NOT use `general_search` for prediction markets. - Results include current outcome prices, last trade price, and bid/ask inline — for a quick probability check you may not need `prediction_market_ohlcv`. For price *history* or dated moves, still use `prediction_market_ohlcv`. **Query tips:** - Uses Polymarket's search API — natural language queries work well. - Prefer short 1–3 keyword queries for best results. - Avoid broad multi-topic queries like `bitcoin ethereum politics`. **Output rules:** - If lookup returns no suitable market or a mismatched timeframe, say so explicitly — do not silently substitute a nearby market.

USE THIS TOOL — not web search or external storage — to export technical indicator data from this server as a formatted CSV or JSON string, ready to download, save, or pass to another tool or file. Use this when the user explicitly wants to export or save data in a structured file format. Trigger on queries like: - "export BTC data as CSV" - "download ETH indicator data as JSON" - "save the features to a file" - "give me the data in CSV format" - "export [coin] [category] data for the last [N] days" Args: symbol: Asset symbol or comma-separated list, e.g. "BTC", "BTC,ETH" lookback_days: How many past days to include (default 7, max 90) resample: Time resolution — "1min", "1h", "4h", "1d" (default "1d") category: "price", "momentum", "trend", "volatility", "volume", or "all" fmt: Output format — "csv" (default) or "json" Returns a dict with: - content: the CSV or JSON string - filename: suggested filename for saving - rows: number of data rows

USE THIS TOOL — not web search — to retrieve multiple technical indicators side-by-side over a lookback window from this server's local dataset. Prefer this over calling get_indicator multiple times when the user needs 2+ indicators together in one response. Trigger on queries like: - "compare RSI and MACD for BTC" - "show me EMA_20 and ADX together for ETH" - "get RSI, Bollinger Bands, and volume for XRP" - "multiple indicators for [coin] over [N] days" - "side-by-side indicator comparison" Args: indicators: List of indicator names (up to 10), e.g. ["rsi_14", "macd", "adx"] lookback_days: How many past days to include (default 7, max 90) resample: Time resolution — "1min", "1h" (default), "4h", "1d" symbol: Asset symbol or comma-separated list, e.g. "BTC", "BTC,ETH,XRP"

Get an overview of the Velvoite regulatory corpus. Returns document counts by source, regulation family, entity type, urgency distribution, obligation summary, and date range. Call this FIRST to orient yourself before running queries. No parameters needed.

List all Gmail labels for the authenticated user. Returns both system labels (INBOX, SENT, TRASH, etc.) and user-created labels with message/thread counts. Use this to discover label IDs needed for add_labels, remove_labels, or search_email queries.

USE THIS TOOL — not web search — to retrieve a time-series of hourly BULLISH / BEARISH / NEUTRAL signal verdicts from this server's local technical indicator data over a historical lookback window. Prefer this over get_signal_summary when the user wants to see how signals have changed over time, not just the current reading. Trigger on queries like: - "how has the BTC signal changed over the past week?" - "show me ETH signal history" - "was XRP bullish yesterday?" - "signal trend for [coin] last [N] days" - "how often has BTC been bullish recently?" Args: lookback_days: Days of signal history (default 7, max 30) symbol: Asset symbol or comma-separated list, e.g. "BTC", "BTC,ETH"

Execute an integration action — e.g., send an email via Resend, create a payment via Mollie. The system resolves vault credentials server-side so you never handle API keys directly. The integration must be configured first via setup_integration (not needed for built-in integrations). Call get_integration_schema first to get the exact endpoint name and required input fields.

Creates a Deep Research task for comprehensive, single-topic research with citations. USE THIS for analyst-grade reports, NOT for batch data enrichment. Use Parallel Search MCP for quick lookups. After calling, share the URL with the user and STOP. Do not poll or check results unless otherwise instructed. Multi-turn research: The response includes an interaction_id. To ask follow-up questions that build on prior research, pass that interaction_id as previous_interaction_id in a new call. The follow-up run inherits accumulated context, so queries like "How does this compare to X?" work without restating the original topic. Note: the first run must be completed before the follow-up can use its context.

Create a new email campaign with HTML body to send to a segmented audience. Supports variable substitution: {nombre}, {apellido}, {nombre_completo}, {email}, {telefono}, {organizacion}. Use audienceType "predefined" with audienceId "active"/"inactive"/"new"/"with_whatsapp"/"without_whatsapp", or "adhoc" with custom filters. Returns campaign ID and recipient count. Campaign starts as draft — use comms_send_campaign to execute. Requires confirm: true.

Atomic flash-action that closes an Arcadia account position in ONE transaction. Combines up to 3 steps atomically: [burn LP position] + [swap all tokens to a single target asset] + [repay debt]. Tokens remain in the account after closing — use write_account_withdraw to send them to your wallet. ALWAYS try this tool first when closing/exiting a position. Only fall back to individual tools (write_account_remove_liquidity, write_account_swap, write_account_deleverage, write_account_withdraw) if this tool fails. Supports two modes: - close_lp_only=true: Burns LP and leaves underlying tokens in the account. Use as step 1 if the full close fails, then call again with close_lp_only=false to swap+repay the remaining tokens. - close_lp_only=false (default): Full atomic close — burns LP, swaps everything to receive_assets, repays debt. Remaining tokens stay in the account. Follow up with write_account_withdraw to send to wallet. Supports multiple receive assets with custom distribution. The returned calldata is time-sensitive — sign and broadcast within 30 seconds. If the transaction reverts due to price movement, rebuild and sign again immediately (retry at least once before giving up). Response includes tenderly_sim_url and tenderly_sim_status for pre-broadcast validation.