"Slack" matching MCP tools:

• automation_test

  Perspective AI

  Runs a single end-to-end execution of an existing automation against a mock conversation, returning success/failure plus the channel target and duration. Mirrors a real production firing. Behavior: - Sends REAL messages by default: posts the configured webhook, sends the configured email, posts the Slack message, or writes the HubSpot record. Use override_email (email channels) or override_webhook (webhook channels) to redirect delivery to a safe test target. - Each call fires another real delivery. - Errors when the perspective or automation is not found, or you do not have access. Webhook URLs (configured or override) are validated. - Mock conversation defaults: trust score 85, status complete, "Test Participant" / test@example.com. Override participant_name, summary, and tags via test_data. - Returns success: true also when the automation's condition skips delivery (e.g., tag/trust filter doesn't match the mock). The error field is populated only on real delivery failures. When to use this tool: - Verifying a freshly-created automation actually delivers before relying on it. PREFER override_email/override_webhook to avoid spamming real recipients. - Reproducing a delivery failure surfaced in automation_list (last_error). When NOT to use this tool: - Listing what's configured — use automation_list. - Changing config — use automation_update. - Removing the automation — use automation_delete.

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• query_knowledge

  mcp-server

  Search the company's connected knowledge across every source — Drive, SharePoint, Confluence, Slack, Notion — with cited synthesized answers, lifecycle awareness, and refusal-on-weak-context. Returns a written answer with [n] citations plus the ranked source chunks. Modes: `fast` (1,500 kT — retrieval-only, no synthesis), `standard` (12,500 kT — default; synthesized answer over the top retrieval set), `deep` (25,000 kT — wider retrieval + premium synthesis for complex questions). Pick the cheapest tier that answers the question. Responses are capped at 25,000 output tokens per Claude Connectors policy; if truncated, structured metadata carries `truncated: true` and `query_id` so the agent can call `get_source_detail` for full provenance.

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• automation_create

  Perspective AI

  Creates an automation on a perspective. Triggers: per_interview (fires on every completed conversation) or scheduled (daily/weekly digest). Channels: webhook, email, slack, hubspot. Execution modes: direct (fast, deterministic) or agent (LLM-powered). Behavior: - Each call creates a new automation — even if name/config matches an existing one. - Once enabled, the automation starts firing on real events: per_interview sends on every completed conversation going forward; scheduled sends a real message on the configured cadence (daily/weekly). - Webhook URLs are validated. For HubSpot, the workspace's HubSpot connection is required — errors with "Could not resolve HubSpot portal ID — please reconnect HubSpot" if not connected. - Errors when the perspective is not found or you do not have access. When to use this tool: - The user wants ongoing notifications on every completed conversation (per_interview). - Building a daily/weekly digest delivered to Slack, email, HubSpot, or a webhook (scheduled). When NOT to use this tool: - Trying a one-off send before going live — create the automation, then use automation_test (use override_email / override_webhook to avoid hitting real recipients). - Editing or toggling an existing automation — use automation_update. - Connecting Slack or HubSpot — use integration_manage first; the provider must be connected before slack/hubspot channels work. Example — per-conversation Slack notify: ``` { "perspective_id": "...", "automation": { "name": "Notify Slack", "trigger": { "type": "per_interview" }, "execution_mode": "agent", "channel": { "type": "composio", "delivery_config": { "provider": "slackbot", "tool_slug": "SLACKBOT_SEND_MESSAGE", "params": { "channel": "#research" }, "resource_id": "...", "resource_name": "..." } } } } ``` Typical flow: 1. integration_manage (operation: "list"/"connect") → ensure Slack / HubSpot is connected (only needed for those channels) 2. automation_create → create the automation 3. automation_test (with overrides) → verify delivery before relying on it

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• xmp4_guide

  xmp4 — Semantic code knowledge for your stack

  Usage guide for xmp4 tools — read this first to learn the correct workflow

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• secret_scan

  AgentSec MCP

  Scan text content for hardcoded secrets, API keys, and credentials using 20 pre-compiled patterns. Privacy guarantee: Input text is NEVER logged, cached, stored, or forwarded. Only findings_count and finding offsets (not matched values) are returned. Detected pattern types include: AWS keys, GitHub/GitLab PATs, OpenAI/Anthropic keys, Stripe secrets, Slack tokens, PEM private keys, JWT tokens, and 13 more. Per-call rate limit: 100/min. Payment: $0.05 USDC per scan.

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• xmp4_grep

  xmp4 — Semantic code knowledge for your stack

  Server-side regex text search over indexed project source files. Free tier: requires file_path (single file). Premium tier (XMP4_PREMIUM_GREP_WALK=true): allows file_glob multi-file walk. Prefer xmp4_tests_for/xmp4_usages for SCIP symbols — grep is for text not indexed (comments, literals, config keys).

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• chieflab_connect_provider

  ChiefLab

  Connect a third-party provider (Zernio, Resend, GA4, Search Console, HubSpot, Stripe, Linear, Notion, Slack) to this workspace. USE WHEN the user wants to wire up publishing, email sending, or analytics readback. For OAuth providers (ga4 / search_console / hubspot) returns an authorizeUrl the agent surfaces to the user. For API-key providers (zernio / resend) returns instructions for the set-key tool. Without this, publish/send/measure tools return 'configure first' errors.

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• RUBE_FIND_RECIPE

  rube

  Find recipes using natural language search. Use this tool when: - User refers to a recipe by partial name, description, or keywords (e.g., "run my GitHub PR recipe", "the slack notification one") - User wants to find a recipe but doesn't know the exact name or ID - You need to find a recipe_id before executing it with RUBE_EXECUTE_RECIPE The tool uses semantic matching to find the most relevant recipes based on the user's query. Input: - query (required): Natural language search query (e.g., "GitHub PRs to Slack", "daily email summary") - limit (optional, default: 5): Maximum number of recipes to return (1-20) - include_details (optional, default: false): Include full details like description, toolkits, tools, and default params Output: - successful: Whether the search completed successfully - recipes: Array of matching recipes sorted by relevance score, each containing: - recipe_id: Use this with RUBE_EXECUTE_RECIPE - name: Recipe name - description: What the recipe does - relevance_score: 0-100 match score - match_reason: Why this recipe matched - toolkits: Apps used (e.g., github, slack) - recipe_url: Link to view/edit - default_params: Default input parameters - total_recipes_searched: How many recipes were searched - query_interpretation: How the search query was understood - error: Error message if search failed Example flow: User: "Run my recipe that sends GitHub PRs to Slack" 1. Call RUBE_FIND_RECIPE with query: "GitHub PRs to Slack" 2. Get matching recipe with recipe_id 3. Call RUBE_EXECUTE_RECIPE with that recipe_id

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• send_workflow_test

  Dreamlit

  Side effect when confirmSend is true: sends one current draft email or Slack message for review, but does not publish, schedule, or edit the workflow. Use after authoring or inspection when the user wants to verify an important message before publishing. Returns sent-test details, app URLs, a confirmation request, or a clarification request with user-facing message choices. Do not expose test target ids as copy; ask users to choose by message label and confirm before sending.

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• RUBE_MULTI_EXECUTE_TOOL

  rube

  Fast and parallel tool executor for tools discovered through RUBE_SEARCH_TOOLS. Use this tool to execute up to 50 tools in parallel across apps only when they're logically independent (no ordering/output dependencies). Response contains structured outputs ready for immediate analysis - avoid reprocessing them via remote bash/workbench tools. Prerequisites: - Always use valid tool slugs and their arguments. NEVER invent tool slugs or argument fields. ALWAYS pass STRICTLY schema-compliant arguments with each tool execution. - Ensure an ACTIVE connection exists for the toolkits that are going to be executed. If none exists, MUST initiate one via RUBE_MANAGE_CONNECTIONS before execution. - Only batch tools that are logically independent - no ordering, no output-to-input dependencies, and no intra-call chaining (tools in one call can't use each other's outputs). DO NOT pass dummy or placeholder inputs; always resolve required inputs using appropriate tools first. Usage guidelines: - If RUBE_SEARCH_TOOLS returns a tool that can perform the task, prefer calling it via this executor. Do not write custom API calls or ad-hoc scripts for tasks that can be completed by available Composio tools. - Prefer parallel execution: group independent tools into a single multi-execute call where possible. - Predictively set sync_response_to_workbench=true if the response may be large or needed for later scripting. It still shows response inline; if the actual response data turns out small and easy to handle, keep everything inline and SKIP workbench usage. - Responses contain structured outputs for each tool. RULE: Small data - process yourself inline; large data - process in the workbench. - ALWAYS include inline references/links to sources in MARKDOWN format directly next to the relevant text. Eg provide slack thread links alongside with summary, render document links instead of raw IDs. Restrictions: Some tools or toolkits may be disabled in this environment. If the response indicates a restriction, inform the user and STOP execution immediately. Do NOT attempt workarounds or speculative actions. - CRITICAL: You MUST always include the 'memory' parameter - never omit it. Even if you think there's nothing to remember, include an empty object {} for memory. Memory Storage: - CRITICAL FORMAT: Memory must be a dictionary where keys are app names (strings) and values are arrays of strings. NEVER pass nested objects or dictionaries as values. - CORRECT format: {"slack": ["Channel general has ID C1234567"], "gmail": ["John's email is john@example.com"]} - Write memory entries in natural, descriptive language - NOT as key-value pairs. Use full sentences that clearly describe the relationship or information. - ONLY store information that will be valuable for future tool executions - focus on persistent data that saves API calls. - STORE: ID mappings, entity relationships, configs, stable identifiers. - DO NOT STORE: Action descriptions, temporary status updates, logs, or "sent/fetched" confirmations. - Examples of GOOD memory (store these): * "The important channel in Slack has ID C1234567 and is called #general" * "The team's main repository is owned by user 'teamlead' with ID 98765" * "The user prefers markdown docs with professional writing, no emojis" (user_preference) - Examples of BAD memory (DON'T store these): * "Successfully sent email to john@example.com with message hi" * "Fetching emails from last day (Sep 6, 2025) for analysis" - Do not repeat the memories stored or found previously.

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• xmp4_callers

  xmp4 — Semantic code knowledge for your stack

  Find direct callers of a symbol in a project. Navigate step-by-step by calling xmp4_callers again on interesting results.

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• get_intelligence_briefs

  supply-chain-intelligence

  Get AI-generated intelligence briefs for each supply chain dimension — energy, materials, transportation, macro, and manufacturing. Each brief provides a narrative analysis of current conditions, key drivers, emerging risks, and recommended watch items. These are not raw data — they are synthesized analytical summaries generated every hour from live data. Designed for decision-makers who need a quick read on each supply chain dimension. Returns structured briefs suitable for executive dashboards, email digests, or Slack channels.

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• slack_join_channel

  Slack_connect

  Join a public Slack channel so the bot can read history and post messages.

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• chieflab_use_manual_fallback

  ChiefLab

  USE WHEN any launch action carries a manualFallback brief — either because the channel has no automated provider at all (Product Hunt, Hacker News, Reddit, Discord, Slack, Indie Hackers, dev.to, YC Bookface, blog) OR because the channel HAS an automated provider but its connector isn't wired yet for this workspace (LinkedIn / X without a Zernio key; email without a Resend key + verified sender domain). Pattern: use the inline fallback NOW to ship the launch manually; connect the provider LATER (each fallback returns an upgradePath with the exact connector wiring) so the same action publishes automatically on the next launch. Returns: paste-ready title + body, per-channel checklist (best time, format, first-comment script), capture-URL-after instruction, measurement template for the 24h readback, and the optional upgradePath when automation is available. Converts a 'blocked' channel into a 5-minute human-in-the-loop ship. Approval-gated upstream: the originating publishAction must already be 'approved' on the reviewUrl before this tool returns the brief.

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• check_message_safety

  Agent Safe Email MCP

  Analyze non-email messages (SMS, WhatsApp, Instagram DMs, Discord, Slack, Telegram, LinkedIn, Facebook Messenger, iMessage, Signal) for platform-specific threats including smishing, wrong-number scams, OTP interception, impersonation, and crypto fraud. $0.01/call via skyfire-api-key header (Skyfire Buyer API Key). By using this service you accept the Terms of Service. Advisory service only.

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• get_intelligence_briefs

  SupplyMaven MCP Server

  Get AI-generated intelligence briefs for each supply chain dimension — energy, materials, transportation, macro, and manufacturing. Each brief provides a narrative analysis of current conditions, key drivers, emerging risks, and recommended watch items. These are not raw data — they are synthesized analytical summaries generated every hour from live data. Designed for decision-makers who need a quick read on each supply chain dimension. Returns structured briefs suitable for executive dashboards, email digests, or Slack channels.

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• xmp4_tests_for

  xmp4 — Semantic code knowledge for your stack

  Find direct tests that exercise a given symbol (direct callers filtered to test-file candidates per language pattern: CSharp/Java/PHP: *Test(s).<ext>; Python: test_*.py / *_test.py; TypeScript/JavaScript: *.spec/test.{ts,js}; Rust: *_tests.rs / tests/; etc.).

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• xmp4_view

  xmp4 — Semantic code knowledge for your stack

  Read a raw file excerpt from an indexed project by line range. Use after xmp4_search/xmp4_outline locates the region of interest, or to expand a truncated xmp4_source snippet. Hard cap of 500 lines per call.

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• slack_channel_history

  Slack_connect

  Get message history from a Slack channel. Bot auto-joins the channel if needed.

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• chieflab_connect_provider

  ChiefLab

  Connect a third-party provider (Zernio, Resend, GA4, Search Console, HubSpot, Stripe, Linear, Notion, Slack) to this workspace. USE WHEN the user wants to wire up publishing, email sending, or analytics readback. For OAuth providers (ga4 / search_console / hubspot) returns an authorizeUrl the agent surfaces to the user. For API-key providers (zernio / resend) returns instructions for the set-key tool. Without this, publish/send/measure tools return 'configure first' errors.

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