Bring Postgres
to LangChain
Learn how to connect ElectricSQL (Sync Engine) to LangChain and start using 2 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
GDPR Free for SubscribersCompatible with every major AI agent and IDE
Gemini
What is the ElectricSQL (Sync Engine) MCP Server?
Connect your ElectricSQL sync engine to any AI agent to stream data directly from Postgres into your conversation context. This server leverages the Electric HTTP Sync API to fetch 'shapes' of data efficiently.
What you can do
- Real-time Sync — Fetch data from Postgres tables with support for initial snapshots and incremental updates using log offsets.
- Shape Management — Define specific subsets of data (shapes) using SQL-like WHERE clauses and precise column selection.
- Live Streaming — Enable long-polling or Server-Sent Events (SSE) to keep your agent updated as data changes in the database.
- Complex Filtering — Use POST-based subset snapshots to handle complex WHERE clauses without hitting URL length limits.
- Pagination & Limits — Efficiently browse large datasets with built-in limit, offset_rows, and order_by support.
How it works
- Subscribe to this server
- Provide your Electric Service URL (e.g., your local or cloud Electric endpoint)
- Start querying your Postgres data directly from Claude, Cursor, or any MCP client
Who is this for?
- Developers — build AI-powered tools that need live access to application data without complex backend plumbing.
- Data Engineers — inspect and sync specific database 'shapes' for analysis or debugging via natural language.
- Product Teams — monitor real-time system state or user activity directly within the AI chat interface.
Built-in capabilities (2)
Use offset=-1 for initial sync. Sync a shape of data out of Postgres via GET
Sync a shape of data out of Postgres via POST (Subset Snapshots)
Why LangChain?
LangChain's ecosystem of 500+ components combines seamlessly with ElectricSQL (Sync Engine) through native MCP adapters. Connect 2 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 ElectricSQL (Sync Engine) 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 ElectricSQL (Sync Engine) queries for multi-turn workflows
ElectricSQL (Sync Engine) in LangChain
ElectricSQL (Sync Engine) and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect ElectricSQL (Sync Engine) 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 | 4,000+ 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 ElectricSQL (Sync Engine) in LangChain
The ElectricSQL (Sync Engine) 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 2 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
ElectricSQL (Sync Engine) for LangChain
Every tool call from LangChain to the ElectricSQL (Sync Engine) MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
How do I perform an initial sync of a database table?
Use the get_shape tool and set the offset parameter to -1. This triggers ElectricSQL to send the full initial snapshot of the specified table.
What should I do if my SQL WHERE clause is too long for a standard URL?
You should use the post_shape tool. It sends the filtering criteria in the request body, which prevents '414 Request-URI Too Long' errors when using complex logic.
Can the AI agent receive updates automatically when data changes in Postgres?
Yes! By setting the live parameter to true in get_shape, the agent can establish a long-polling connection to stream incremental changes as they happen.
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
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