Bring Codebase Intelligence
to LangChain
Learn how to connect Greptile to LangChain and start using 11 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
What is the Greptile MCP Server?
Connect your Greptile account to any AI agent and unlock AI-powered codebase understanding through natural conversation.
What you can do
- AI Codebase Q&A — Ask natural language questions about one or more repositories and receive AI-generated answers with code references
- Contextual Follow-ups — Continue conversations with session context for multi-turn codebase exploration
- Semantic Code Search — Search across indexed repositories to find relevant files, functions, and code patterns
- File-Specific Search — Target searches within a specific file path for precise results
- Repository Indexing — Submit GitHub or GitLab repositories for indexing, check progress, and trigger re-indexing
- Repository Management — List all indexed repos, inspect file metadata, and remove outdated indexes
- Usage Monitoring — Track API consumption and rate limits
How it works
1. Subscribe to this server
2. Enter your Greptile API Key from the developer dashboard
3. Start querying your codebase from Claude, Cursor, or any MCP-compatible client
Who is this for?
- Developers — understand unfamiliar codebases, find implementations, and navigate large repositories through conversation
- Code Reviewers — search for related patterns, understand code context, and trace dependencies
- Engineering Managers — get quick answers about architecture decisions, coding patterns, and technical debt
Built-in capabilities (11)
Delete indexed repository
Get file info
Check API usage
Get repository status
Index a repository
List indexed repositories
Query codebase with AI
Query with session context
Reindex a repository
Search in specific file
Search codebase
Why LangChain?
LangChain's ecosystem of 500+ components combines seamlessly with Greptile through native MCP adapters. Connect 11 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.
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The largest ecosystem of integrations, chains, and agents. combine Greptile MCP tools with 500+ LangChain components
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Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step
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LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging
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Memory and conversation persistence let agents maintain context across Greptile queries for multi-turn workflows
Greptile in LangChain
Greptile and 3,400+ other MCP servers. One platform. One governance layer.
Teams that connect Greptile to LangChain through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 3,400+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for Greptile in LangChain
The Greptile 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. All 11 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in LangChain only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.
* 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
How Vinkius secures
Greptile for LangChain
Every tool call from LangChain to the Greptile MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can I ask natural language questions about my codebase?
Yes! The query_codebase tool sends a natural language question along with repository references and returns AI-generated answers with specific code references (file paths and line numbers). For follow-up questions, use query_with_context with the session ID from the previous response to maintain conversation continuity.
Do I need to index my repository before querying it?
Yes. Use index_repository with the remote host (github or gitlab), repository path (owner/repo), and branch name. Check indexing progress with get_repository_status. Once indexed, you can query and search the repository. Use reindex_repository to refresh the index after significant code changes.
Can I search for specific code patterns across my repositories?
Yes. The search_codebase tool performs semantic search across your indexed repositories to find relevant files and functions. For targeted results, use search_by_filepath to narrow the search to a specific file path. Use get_file_info to retrieve indexed metadata for any file.
How does LangChain connect to MCP servers?
Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.
Which LangChain agent types work with MCP?
All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.
Can I trace MCP tool calls in LangSmith?
Yes. All MCP tool invocations appear as traced steps in LangSmith, showing input parameters, response payloads, latency, and token usage.
MultiServerMCPClient not found
Install: pip install langchain-mcp-adapters