Runbear

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.