Vectara MCP Server for VS Code Copilot 7 tools — connect in under 2 minutes
GitHub Copilot in VS Code is the most widely adopted AI coding assistant, embedded directly into the world's most popular code editor. With MCP support in Agent mode, Copilot can access external data and APIs to generate context-aware code grounded in real-time information.
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{
"mcpServers": {
"vectara": {
"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
}
}
}
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Vectara MCP Server
Connect your Vectara environment to any AI agent to unlock enterprise-grade Retrieval-Augmented Generation (RAG) and semantic search directly inside your conversational IDE or workspace.
GitHub Copilot Agent mode brings Vectara data directly into your VS Code workflow. With a project-scoped config, the entire team shares access to 7 tools. Copilot queries live data, generates typed code, and writes tests from actual API responses, all without leaving the editor.
What you can do
- Semantic Search — Query your indexed private corpora naturally and return highly relevant, grounded documents without traditional keyword matching limitations.
- Conversational RAG — Execute fully-fledged interactive chats leveraging Vectara's backend to provide detailed, cited answers strictly based on your secure documents.
- Corpus Management — List all available data corpora, retrieve unique keys, and discover the shape of your indexed data environment on the fly.
- Document Auditing — Monitor specific document indexes within a corpus, verify correct ingestions, or permanently delete obsolete files avoiding polluted search results.
The Vectara MCP Server exposes 7 tools through the Vinkius. Connect it to VS Code Copilot in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Vectara to VS Code Copilot via MCP
Follow these steps to integrate the Vectara MCP Server with VS Code Copilot.
Create MCP config
Create a .vscode/mcp.json file in your project root
Add the server config
Paste the JSON configuration above
Enable Agent mode
Open GitHub Copilot Chat and switch to Agent mode using the dropdown
Start using Vectara
Ask Copilot: "Using Vectara, help me...". 7 tools available
Why Use VS Code Copilot with the Vectara MCP Server
GitHub Copilot for Visual Studio Code provides unique advantages when paired with Vectara through the Model Context Protocol.
VS Code is used by over 70% of developers. adding MCP tools to Copilot means your team can leverage external data without leaving their primary editor
Project-scoped MCP configs (`.vscode/mcp.json`) let you commit server configurations to your repository, ensuring the entire team shares the same tool access
Copilot's Agent mode integrates MCP tools seamlessly with file editing, terminal commands, and workspace search in a single agentic loop
GitHub's enterprise compliance and audit features extend to MCP tool usage, providing visibility into how AI interacts with external services
Vectara + VS Code Copilot Use Cases
Practical scenarios where VS Code Copilot combined with the Vectara MCP Server delivers measurable value.
Live API integration: Copilot can query an MCP server, inspect the response schema, and generate typed API client code in the same step
DevSecOps workflows: security teams can give developers access to domain intelligence tools directly in their editor for real-time vulnerability assessment during code review
Data pipeline development: Copilot fetches sample data via MCP and generates transformation scripts, validators, and test fixtures from actual API responses
Documentation generation: Copilot queries available tools and auto-generates README sections, API reference docs, and usage examples
Vectara MCP Tools for VS Code Copilot (7)
These 7 tools become available when you connect Vectara to VS Code Copilot via MCP:
delete_corpus_document
This action is irreversible. Permanently removes a document from a corpus
execute_rag_chat
Provide corpus keys and the user query to get a summarized AI response with citations. Executes a RAG-powered chat completion
get_corpus_details
Retrieves metadata and configuration for a specific corpus
list_chat_sessions
Lists previous RAG chat sessions
list_corpora
Lists all corpora (searchable datasets) in the Vectara account
list_corpus_documents
Lists all indexed documents within a specific corpus
perform_semantic_search
Provide one or more comma-separated corpus keys and the query text. Executes a semantic search across one or more corpora
Example Prompts for Vectara in VS Code Copilot
Ready-to-use prompts you can give your VS Code Copilot agent to start working with Vectara immediately.
"List all configured knowledge corpora I have in Vectara."
"Query corpus `cor-81a` for instructions on 'rolling back kubernetes pods' and show only the top 3 best matching results."
"List all active chat context session IDs for the last week."
Troubleshooting Vectara MCP Server with VS Code Copilot
Common issues when connecting Vectara to VS Code Copilot through the Vinkius, and how to resolve them.
MCP tools not available
Vectara + VS Code Copilot FAQ
Common questions about integrating Vectara MCP Server with VS Code Copilot.
Which VS Code version supports MCP?
How do I switch to Agent mode?
Can I restrict which MCP tools Copilot can access?
Does MCP work in VS Code Remote or Codespaces?
.vscode/mcp.json work in Remote SSH, WSL, and GitHub Codespaces environments. The MCP connection is established from the remote host, so ensure the server URL is accessible from that environment.Connect Vectara with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
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Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
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TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Vectara to VS Code Copilot
Get your token, paste the configuration, and start using 7 tools in under 2 minutes. No API key management needed.