Overview
The Grapevine MCP provides 2 categories of tools that can be used to query your Company Context: Search Tools are the core tools, intended to be used by an agent to find specific documents that match a query. These tools are intended to be used in sequence, and execute quickly. They are modeled after the tools that applications like Claude Code or Cline use to navigate a codebase. In addition to the Search Tools, we provide a pre-packaged Agent Tool that is adept at using the Search Tools to research your Company Context and answer arbitrary questions.Configuration
Grapevine runs as a remote MCP server at:Available tools
Search tools
These tools provide direct access to search and retrieve documents from your organization’s knowledge base.semantic_search
semantic_search
Search your organization’s internal context for conceptually similar content using AI embeddings. Use this when you need to find documents that are semantically related to your query, even if they don’t contain exact keyword matches.
- Request
- Response
Natural language query to search for semantically similar content
Maximum number of results to return (min: 1, max: 100)
Filters to narrow down results. See SearchFilters for complete structure and available options
keyword_search
keyword_search
Search your organization’s internal context for documents containing specific keywords or phrases. Supports both natural language queries and advanced OpenSearch syntax.
- Request
- Response
Search query
- Standard mode: Natural language keywords
- Advanced mode: OpenSearch syntax with operators (
AND,OR,NOT,+,-, wildcards*, field queriesfield:value, grouping with parentheses, fuzzy search~, boosting^)
Maximum number of results to return (min: 1, max: 100)
Filters to narrow down results. See SearchFilters for complete structure and available options
Enable advanced OpenSearch query syntax
get_document
get_document
Retrieve the full raw text content of a specific document from your organization’s internal context. Use this when you have a document ID from search results and need the complete document text.
- Request
- Response
Document identifier. Format varies by connector. See Document Sources and IDs for details
get_document_metadata
get_document_metadata
Retrieve metadata for a document without downloading its full text content. Use this when you only need document information like source, dates, and metadata fields.
- Request
- Response
Document identifier. Format varies by connector. See Document Sources and IDs for details
For complete details on document sources, ID formats, filters, and data structures, see the API Reference.
Agent Tools
ask_agent
ask_agent
This is the simplest way to get a comprehensive answer with citations - it is a good starting point for complex queries that require reasoning and synthesis across multiple documents.
ask_agent is akin to a Deep Research Agent - it is slow, thorough, and will answer with citations to the documents that were used to answer the question. Make sure your client is ready for large (100k+ tokens) and slow (multi-minute) responses.- Request
- Response
User question to answer with agentic search
Optional file attachments as list of objects with:
name(string) - Filenamemimetype(string) - MIME typecontent(string) - Base64 encoded file content
Prior response ID to continue a conversation
Output format: use
'slack' for Slack markdown formattingOverride the default system prompt
OpenAI reasoning effort level:
'minimal', 'low', 'medium', or 'high'Response detail level:
'low', 'medium', or 'high'ask_agent_streaming
ask_agent_streaming
Streaming variant of
ask_agent that returns events as they occur. Use this when you need real-time progress updates during agentic search.- Request
- Response
Same as
ask_agent above.