{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"awesome-runbear","slug":"runbear","name":"Runbear","type":"mcp","url":"https://runbear.io/solutions/integrations/slack/mcp","page_url":"https://unfragile.ai/runbear","categories":["mcp-servers","app-builders"],"tags":[],"pricing":{"model":"unknown","free":false,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"awesome-runbear__cap_0","uri":"capability://tool.use.integration.slack.native.mcp.client.with.chat.based.agent.invocation","name":"slack-native mcp client with chat-based agent invocation","description":"Runbear embeds an MCP client directly into Slack's messaging interface, allowing users to invoke AI agents and trigger tool calls through natural chat commands without leaving the workspace. The system translates Slack messages into MCP tool requests, executes them against integrated services, and returns results as formatted Slack messages. This eliminates context-switching and enables team-wide access to automated workflows through a familiar chat UX.","intents":["Invoke AI agents from Slack to automate cross-tool workflows without switching applications","Enable non-technical team members to trigger complex integrations through chat commands","Route requests to specific agents based on channel or mention patterns","Retrieve information from multiple integrated services and surface results in Slack threads"],"best_for":["Teams using Slack as their primary communication hub who want to reduce tool-switching overhead","Organizations with non-technical users who need access to automated workflows","Companies managing multiple SaaS tools (CRM, ticketing, docs) and seeking unified access"],"limitations":["Slack-first design means limited native support for Teams/Discord workflows despite claims of support","Message length and formatting constraints of Slack API may truncate complex tool outputs","No documented support for interactive Slack modals or rich UI components for complex workflows","Rate-limited by Slack's API quotas (60 messages per minute per workspace)"],"requires":["Active Slack workspace with admin permissions to install apps","API key for at least one supported AI model (Anthropic Claude, OpenAI, Google Gemini, or Perplexity)","OAuth credentials for each integrated service (HubSpot, Jira, Linear, etc.)"],"input_types":["natural language chat messages","slash commands","mentions and thread replies"],"output_types":["formatted Slack messages","thread replies with structured data","links to created resources (tickets, docs)"],"categories":["tool-use-integration","automation-workflow","chat-interface"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-runbear__cap_1","uri":"capability://tool.use.integration.multi.service.ticket.and.issue.creation.with.context.preservation","name":"multi-service ticket and issue creation with context preservation","description":"Runbear enables users to create tickets in Jira or Linear directly from Slack conversations, automatically extracting context from the chat thread (participants, discussion history, attachments) and populating ticket fields. The system maps Slack message content to ticket schemas, handles OAuth authentication to target systems, and returns ticket links back to Slack. This capability supports mutating operations across multiple ticketing platforms with a single chat command.","intents":["Convert Slack discussions into tracked Jira/Linear tickets without manual copying of context","Create tickets with pre-populated fields (assignee, labels, description) inferred from conversation","Route ticket creation to different systems based on project or team context","Maintain bidirectional awareness between Slack conversations and ticket systems"],"best_for":["Engineering teams using Jira or Linear who want to reduce ticket creation friction","Support teams converting customer conversations into tracked issues","Cross-functional teams needing to escalate Slack discussions into formal tracking systems"],"limitations":["Ticket field mapping is not documented — unclear which Slack message elements map to which ticket fields","No support for custom ticket fields or complex workflow states beyond basic creation","Requires separate OAuth setup for each Jira/Linear workspace; no multi-workspace orchestration documented","No rollback or undo mechanism if ticket creation fails mid-operation"],"requires":["Slack workspace with Runbear app installed","OAuth token for Jira or Linear with 'create issue' permissions","AI model API key (for context extraction and field mapping)"],"input_types":["Slack message thread","natural language command with optional parameters","message reactions or slash commands"],"output_types":["Jira issue URL","Linear issue URL","confirmation message with ticket metadata"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-runbear__cap_10","uri":"capability://tool.use.integration.microsoft.teams.and.discord.chat.platform.support","name":"microsoft teams and discord chat platform support","description":"Runbear claims to support Microsoft Teams and Discord in addition to Slack, embedding the MCP client in these chat platforms and enabling the same agent invocation and tool orchestration workflows. The system adapts the Slack-native interface to Teams and Discord APIs, handling platform-specific message formatting and authentication. This enables organizations using Teams or Discord to access the same automation capabilities as Slack users.","intents":["Use Runbear in Microsoft Teams environments without switching to Slack","Enable Discord communities to automate workflows through chat","Maintain consistent automation experience across multiple chat platforms"],"best_for":["Organizations standardized on Microsoft Teams or Discord","Multi-platform teams wanting consistent automation across chat tools"],"limitations":["Teams and Discord support is claimed but not documented with technical details","Feature parity with Slack version is not documented — unclear if all capabilities work on Teams/Discord","Teams and Discord API differences may limit functionality (e.g., Teams lacks some Slack features)","No documented support for Teams channels, Discord roles, or platform-specific permission models","Setup and configuration process for Teams/Discord is not documented"],"requires":["Microsoft Teams workspace or Discord server with admin permissions","OAuth credentials for Teams/Discord app installation"],"input_types":["Teams messages or Discord messages","slash commands in Teams/Discord"],"output_types":["Teams messages or Discord messages with results","links to created resources"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-runbear__cap_11","uri":"capability://safety.moderation.encrypted.credential.storage.and.data.protection.in.transit.and.at.rest","name":"encrypted credential storage and data protection in transit and at rest","description":"Runbear claims to encrypt API credentials and sensitive data both in transit (TLS) and at rest, and claims not to store sensitive content beyond what is needed for operations. The system manages OAuth tokens and API keys for integrated services, encrypting them before storage and using them only when invoking tools. This protects against credential exposure and unauthorized access to integrated systems.","intents":["Securely store API keys and OAuth tokens for integrated services","Prevent credential exposure in logs, error messages, or Slack history","Comply with security standards (SOC 2, encryption requirements)"],"best_for":["Organizations with strict security and compliance requirements","Teams handling sensitive customer or payment data"],"limitations":["Encryption implementation details are not documented — unclear which algorithms or key management practices are used","Data retention policies are not documented — unclear how long credentials are stored or when they are deleted","No documented support for credential rotation or expiration","No audit trail or logging of credential access","SOC 2 compliance is claimed but not verified; no audit report or certification details provided","No documented support for customer-managed encryption keys (CMEK)"],"requires":["Runbear subscription with security features enabled","Trust in Runbear's encryption and data handling practices"],"input_types":["API keys and OAuth tokens during setup"],"output_types":["encrypted storage of credentials","secure transmission of credentials to integrated services"],"categories":["safety-moderation","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-runbear__cap_2","uri":"capability://tool.use.integration.crm.record.mutation.and.enrichment.from.chat.context","name":"crm record mutation and enrichment from chat context","description":"Runbear enables users to create and update CRM records (HubSpot, Attio) directly from Slack conversations, mapping chat participants and discussion content to CRM contact/company fields. The system uses the AI model to extract relevant information from messages, authenticate to CRM APIs, and perform create/update operations. This allows teams to maintain CRM data freshness without leaving Slack or manually entering information into separate systems.","intents":["Create new CRM contacts or companies from Slack conversations about customers or prospects","Update existing CRM records with new information discussed in Slack (deal status, notes, interactions)","Enrich CRM data with conversation context and participant information automatically","Maintain single source of truth for customer information across Slack and CRM"],"best_for":["Sales teams using HubSpot or Attio who want to reduce manual CRM data entry","Customer success teams tracking customer interactions and updates in real-time","Organizations where Slack is the primary communication channel and CRM is secondary"],"limitations":["CRM field mapping is not documented — unclear which Slack message elements map to which CRM fields","No support for custom CRM fields or complex field types (multi-select, linked records)","Requires OAuth setup for each CRM instance; no multi-workspace or multi-account orchestration","No conflict resolution if CRM record is simultaneously updated elsewhere","Limited to HubSpot and Attio; no Salesforce, Pipedrive, or other CRM support documented"],"requires":["Slack workspace with Runbear app installed","OAuth token for HubSpot or Attio with 'create/update contact' and 'create/update company' permissions","AI model API key for information extraction"],"input_types":["Slack message thread","natural language command with optional CRM record ID","message reactions or slash commands"],"output_types":["CRM record URL (HubSpot contact/company link, Attio record link)","confirmation message with updated field values","error message if record creation/update fails"],"categories":["tool-use-integration","data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-runbear__cap_3","uri":"capability://search.retrieval.cross.tool.knowledge.retrieval.and.semantic.search.from.slack","name":"cross-tool knowledge retrieval and semantic search from slack","description":"Runbear enables users to query information across integrated knowledge sources (Google Drive, Notion, Linear, HubSpot, Fireflies, Attio, Confluence, Gmail) directly from Slack chat. The system performs semantic search across these sources using embeddings, retrieves relevant documents/records, and returns formatted results in Slack. This is a read-only capability that aggregates information from multiple tools without requiring users to navigate each system separately.","intents":["Search across company knowledge bases (Notion, Confluence, Google Drive) from Slack without switching apps","Retrieve customer information from CRM (HubSpot, Attio) during customer conversations","Find relevant meeting notes or transcripts (Fireflies) to answer questions in real-time","Query historical email or document content (Gmail, Google Docs) to provide context in discussions"],"best_for":["Teams with distributed knowledge across multiple SaaS tools who want unified search","Customer-facing teams (support, sales) who need quick access to customer/product information","Organizations where Slack is the primary communication hub and knowledge is fragmented"],"limitations":["Semantic search quality depends on embedding model and indexing strategy — not documented","No documented support for real-time indexing; search may return stale results if sources are not regularly re-indexed","Search results limited by Slack message length constraints; complex results may be truncated","No support for full-text search or advanced query syntax; limited to natural language queries","Requires OAuth setup for each knowledge source; no batch indexing or scheduled crawling documented"],"requires":["Slack workspace with Runbear app installed","OAuth tokens for each knowledge source (Google Drive, Notion, Linear, HubSpot, Fireflies, Attio, Confluence, Gmail)","AI model API key for semantic search and result ranking"],"input_types":["natural language search queries in Slack","slash commands with search parameters","message mentions or thread context"],"output_types":["formatted Slack messages with search results","links to source documents/records","snippets of relevant content with context"],"categories":["search-retrieval","memory-knowledge","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-runbear__cap_4","uri":"capability://automation.workflow.automated.email.parsing.and.gmail.inbox.monitoring.with.action.triggers","name":"automated email parsing and gmail inbox monitoring with action triggers","description":"Runbear monitors Gmail inboxes for incoming emails, parses email content using the AI model, and triggers automated actions (e.g., auto-replies, ticket creation, CRM updates) based on email content patterns. The system integrates with Gmail API for inbox monitoring, uses NLP to extract intent and entities from email bodies, and orchestrates downstream actions through MCP tools. This enables email-driven automation workflows without manual intervention.","intents":["Auto-reply to incoming emails with templated responses based on email content","Create support tickets automatically when customer emails arrive in specific inboxes","Update CRM records when customer emails are received (e.g., mark as contacted)","Route emails to appropriate team members or channels based on content analysis"],"best_for":["Support teams managing high-volume inboxes who want to automate routine responses","Sales teams who want to track customer emails in CRM automatically","Organizations using email as a primary communication channel for customer interactions"],"limitations":["Email parsing rules and action triggers are not documented — unclear how email content maps to actions","No support for complex email parsing (attachments, embedded images, forwarded chains)","Gmail API rate limits may prevent real-time monitoring of large inboxes (15 requests per second per user)","Auto-reply functionality may violate email best practices or spam filters if not carefully configured","No support for other email providers (Outlook, custom SMTP); Gmail-only","Requires Gmail OAuth with 'modify' permissions — security risk if not properly scoped"],"requires":["Slack workspace with Runbear app installed","Gmail account with OAuth token granting 'modify' permissions","AI model API key for email content parsing and intent extraction"],"input_types":["incoming Gmail messages","email content (subject, body, sender, attachments metadata)"],"output_types":["auto-reply emails sent to Gmail","tickets created in Jira/Linear","CRM records updated","Slack notifications about processed emails"],"categories":["automation-workflow","tool-use-integration","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-runbear__cap_5","uri":"capability://tool.use.integration.stripe.payment.operations.and.refund.lookups.from.chat","name":"stripe payment operations and refund lookups from chat","description":"Runbear enables users to query Stripe for payment information (refund status, subscription details) and perform mutations (issue refunds, update subscriptions) directly from Slack. The system authenticates to Stripe API using provided credentials, translates natural language requests into Stripe API calls, and returns formatted results in Slack. This allows finance and support teams to manage payments without leaving the chat interface.","intents":["Look up refund status for a customer without navigating Stripe dashboard","Issue refunds directly from Slack during customer support conversations","Update customer subscriptions (pause, cancel, upgrade) from chat","Retrieve payment history or invoice information for a customer"],"best_for":["Support teams handling payment-related customer requests","Finance teams managing refunds and subscription changes","SaaS companies where Slack is the primary operational hub"],"limitations":["Stripe API operations supported are not documented — unclear which Stripe endpoints are exposed","No support for complex payment operations (partial refunds, payment plan creation, dunning management)","Requires Stripe API key with sensitive permissions (read/write charges, refunds, subscriptions) — security risk if key is compromised","No audit trail or approval workflow for sensitive operations like refunds","Stripe rate limits (100 requests per second) may be exceeded in high-volume scenarios","No support for other payment processors (PayPal, Square, Adyen)"],"requires":["Slack workspace with Runbear app installed","Stripe API key with 'read' and 'write' permissions for charges, refunds, and subscriptions","AI model API key for natural language to Stripe API translation"],"input_types":["natural language requests (e.g., 'refund customer X', 'check subscription status for Y')","slash commands with customer/payment identifiers","message mentions or thread context"],"output_types":["refund confirmation with transaction ID","subscription status or update confirmation","payment history or invoice links","error messages if operation fails"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-runbear__cap_6","uri":"capability://tool.use.integration.ai.agent.selection.and.model.routing.with.multi.provider.support","name":"ai agent selection and model routing with multi-provider support","description":"Runbear allows users to select and configure AI agents with different underlying models (Anthropic Claude, OpenAI GPT, Google Gemini, Perplexity) and route requests to specific agents based on context. The system manages API keys for multiple providers, handles model-specific request/response formatting, and enables users to choose agents based on task requirements (cost, latency, capability). This provides flexibility in AI model selection without vendor lock-in.","intents":["Select different AI models for different tasks (e.g., Claude for reasoning, GPT for speed)","Route requests to cost-optimized models for high-volume operations","Use specialized models for specific domains (e.g., Perplexity for research-heavy tasks)","Switch models without reconfiguring integrations or workflows"],"best_for":["Organizations wanting to avoid vendor lock-in with a single AI provider","Teams with cost-sensitive operations who want to optimize model selection per task","Advanced users who understand model trade-offs (cost, latency, capability)"],"limitations":["Model routing logic is not documented — unclear how requests are routed to specific agents","No support for model fallback or retry logic if primary model fails","Requires separate API keys for each provider; no unified credential management","Model-specific prompt engineering may be required; no automatic prompt adaptation across models","No documented support for fine-tuned or custom models","Pricing varies significantly across providers; no cost estimation or optimization guidance"],"requires":["Slack workspace with Runbear app installed","API keys for at least one supported model provider (Anthropic, OpenAI, Google, Perplexity)","Understanding of model capabilities and trade-offs to make informed selection"],"input_types":["agent selection during setup","model preference in chat commands","configuration parameters for agent behavior"],"output_types":["agent configuration confirmation","model-specific responses in Slack","usage metrics and cost tracking (if available)"],"categories":["tool-use-integration","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-runbear__cap_7","uri":"capability://text.generation.language.document.generation.and.auto.drafting.from.chat.context","name":"document generation and auto-drafting from chat context","description":"Runbear enables users to generate documents (proposals, reports, contracts) directly from Slack conversations, using the AI model to synthesize chat context into structured document content. The system creates documents in Google Docs or other supported platforms, populates them with AI-generated content based on conversation history, and returns document links in Slack. This eliminates manual document creation and ensures documents reflect the latest discussion context.","intents":["Generate proposal documents from sales conversations in Slack","Auto-draft meeting notes or reports from discussion threads","Create contract templates populated with information from customer conversations","Generate documentation from technical discussions without manual writing"],"best_for":["Sales teams who want to quickly generate proposals from customer conversations","Project teams who want to auto-generate meeting notes and status reports","Organizations where Slack is the primary discussion medium and documents are secondary outputs"],"limitations":["Document generation templates and content mapping are not documented","No support for complex document structures (multi-section reports, tables, embedded media)","Generated content quality depends on conversation clarity and AI model capability — may require manual editing","No version control or change tracking for generated documents","Limited to Google Docs; no support for Word, PDF, or other formats","No support for document signing or approval workflows"],"requires":["Slack workspace with Runbear app installed","Google Drive OAuth token with 'create documents' permission","AI model API key for document content generation"],"input_types":["Slack message thread or conversation history","natural language command with document type (proposal, report, contract)","optional parameters for document structure or tone"],"output_types":["Google Docs link with auto-generated content","confirmation message with document summary","error message if document generation fails"],"categories":["text-generation-language","automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-runbear__cap_8","uri":"capability://safety.moderation.role.based.access.control.and.sso.integration.for.team.governance","name":"role-based access control and sso integration for team governance","description":"Runbear provides role-based access control (RBAC) and single sign-on (SSO) integration to manage which team members can invoke specific agents, access certain integrations, or perform sensitive operations. The system enforces permissions at the agent and tool level, integrating with enterprise SSO providers for centralized identity management. This enables organizations to govern AI agent usage and prevent unauthorized access to sensitive integrations.","intents":["Restrict refund operations to finance team members only","Limit CRM access to sales and customer success teams","Prevent non-technical users from invoking code-related agents","Centralize identity management using enterprise SSO (Okta, Azure AD, etc.)"],"best_for":["Enterprise organizations with strict access control requirements","Teams with sensitive operations (payments, customer data) that require permission enforcement","Organizations using enterprise SSO providers for centralized identity management"],"limitations":["RBAC and SSO implementation details are not documented — unclear how permissions are enforced","No documented support for fine-grained permissions (e.g., 'refund up to $100' vs 'refund any amount')","SSO provider support is not specified — unclear which providers are supported","No audit trail or logging of permission checks or access denials","Permission changes may not be real-time; caching or eventual consistency may apply","No support for temporary permission elevation or approval workflows"],"requires":["Slack workspace with Runbear app installed","Enterprise SSO provider (Okta, Azure AD, Google Workspace, etc.) for identity management","Admin access to configure roles and permissions"],"input_types":["role definitions during setup","permission assignments per user or group","SSO provider configuration"],"output_types":["permission enforcement at agent/tool invocation time","error messages if user lacks required permissions","audit logs of permission checks (if available)"],"categories":["safety-moderation","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-runbear__cap_9","uri":"capability://automation.workflow.plan.based.resource.quotas.and.credit.consumption.tracking","name":"plan-based resource quotas and credit consumption tracking","description":"Runbear implements a tiered pricing model with plan-based quotas for agents, documents, and 'interactors' (monthly active users), and tracks credit consumption for API calls and operations. The system enforces quotas at runtime, preventing operations that exceed plan limits, and provides usage dashboards for monitoring consumption. This enables organizations to control costs and prevent unexpected overages.","intents":["Limit number of AI agents per team based on subscription tier","Cap monthly active users to control per-seat costs","Track API credit consumption across integrations and operations","Prevent operations that would exceed plan quotas"],"best_for":["Organizations with cost-conscious operations who want to control spending","Teams scaling usage gradually and wanting to upgrade plans as needed","Finance teams who need visibility into AI/automation spending"],"limitations":["Quota enforcement mechanism is not documented — unclear how limits are enforced in real-time","Credit consumption mapping is not documented — unclear which operations consume how many credits","No support for custom quotas or overage handling; unclear what happens when quotas are exceeded","No documented support for quota sharing across teams or projects","Usage dashboards and reporting are not documented","No support for reserved capacity or volume discounts"],"requires":["Runbear subscription with specific plan tier (Starter, Professional, Enterprise)","Admin access to view usage and manage quotas"],"input_types":["plan selection during signup","quota configuration per team or project"],"output_types":["quota enforcement at operation time","error messages if quota exceeded","usage dashboards and reports (if available)"],"categories":["automation-workflow","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":30,"verified":false,"data_access_risk":"high","permissions":["Active Slack workspace with admin permissions to install apps","API key for at least one supported AI model (Anthropic Claude, OpenAI, Google Gemini, or Perplexity)","OAuth credentials for each integrated service (HubSpot, Jira, Linear, etc.)","Slack workspace with Runbear app installed","OAuth token for Jira or Linear with 'create issue' permissions","AI model API key (for context extraction and field mapping)","Microsoft Teams workspace or Discord server with admin permissions","OAuth credentials for Teams/Discord app installation","Runbear subscription with security features enabled","Trust in Runbear's encryption and data handling practices"],"failure_modes":["Slack-first design means limited native support for Teams/Discord workflows despite claims of support","Message length and formatting constraints of Slack API may truncate complex tool outputs","No documented support for interactive Slack modals or rich UI components for complex workflows","Rate-limited by Slack's API quotas (60 messages per minute per workspace)","Ticket field mapping is not documented — unclear which Slack message elements map to which ticket fields","No support for custom ticket fields or complex workflow states beyond basic creation","Requires separate OAuth setup for each Jira/Linear workspace; no multi-workspace orchestration documented","No rollback or undo mechanism if ticket creation fails mid-operation","Teams and Discord support is claimed but not documented with technical details","Feature parity with Slack version is not documented — unclear if all capabilities work on Teams/Discord","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.34,"ecosystem":0.35000000000000003,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.15,"match_graph":0.23,"freshness":0.12}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-06-17T09:51:04.048Z","last_scraped_at":"2026-05-03T14:00:18.053Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=runbear","compare_url":"https://unfragile.ai/compare?artifact=runbear"}},"signature":"ldsvwy15vhvg9n2kg+JqfPJakeOV0W2nKvcayiYnuOrb7CWAHlxE4BzT7VYvnCqrrNcmL1E6VHmmqrWrRJAcAA==","signedAt":"2026-06-21T01:37:01.548Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/runbear","artifact":"https://unfragile.ai/runbear","verify":"https://unfragile.ai/api/v1/verify?slug=runbear","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}