Bitquery MCP Server on-chain data for your AI agents, in plain English.
Connect mcp.bitquery.ioto Claude, Cursor or any MCP client and ask Bitquery's on-chain trading dataset anything — in plain English. The agent resolves your question to an MCP tool call and gets back real rows: DEX trades, prices, balances, holders and money flow across 40+ chains. No GraphQL to hand-write.
Connect the client you already use.
Because mcp.bitquery.io speaks the standard Model Context Protocol, any MCP-compatible client connects out of the box — over a remote HTTP/SSE transport or a local stdio bridge via mcp-remote. Authorize once over OAuth, then ask on-chain questions.
Claude
Add the server in Claude Desktop, Web or Claude Code, authorize once over OAuth, then ask on-chain questions straight from chat.
Cursor
Drop the server into .cursor/mcp.json via mcp-remote and your coding agent can pull live trades, balances and holders inline.
VS Code
Connect the MCP server to VS Code's agent mode over the same hosted endpoint — no node, no indexer to run.
Windsurf
Any MCP-compatible client — Windsurf and custom agents included — speaks to mcp.bitquery.io out of the box.
A small, typed tool surface for your agent.
The server exposes a handful of typed tools — the LLM uses them to discover what's in the dataset and pull rows. A plain-English prompt maps to one tool call with typed params; no hallucinated schema, no GraphQL to hand-write.
# "Show the latest WETH/USDC trades on Uniswap" dex_trades({ network: "eth", protocol: "uniswap_v3", pair: "WETH/USDC", orderBy: "Block_Time desc", limit: 25 })
Your agent shouldn't have to learn a query language to read the chain.
Wiring an LLM to on-chain data usually means teaching it a schema, writing GraphQL by hand, running an indexer and parsing raw logs — then babysitting it when the agent hallucinates a field. The Bitquery MCP server exposes the data as tools, so the agent just asks in plain English and gets clean, typed rows back.
The agents people ship on the MCP server.
Each one is the same MCP server plugged into a different client — connect once, then let the agent ask on-chain questions for you.
Build an AI trading agent
Let an agent pull live DEX trades, OHLC and new-token launches, then reason over them — "which Base tokens crossed $10M market cap in the last 24h?"
On-chain research copilot
Trace money flow, rank token holders and pull wallet history in plain English — the audit and investigation workflow without GraphQL.
Plug into Claude or Cursor
Add the server to Claude Code or your .cursor/mcp.json, authorize once over OAuth, then ask on-chain questions straight from chat.
What teams say about our data
"We did a thorough search of the market for the best onchain data. Bitquery came out on top — and now powers all live prices across Nansen. We don't think of them as a vendor. They're a partner."
Bitquery does the hard work of parsing blockchain transaction data into a usable form so that we don't have to. We use their interface to diagnose issues with complex transactions and their analytics as a starting point for our own.
They proved they had the technology to deliver sophisticated data solutions. We extended our support through the Binance X fellowship — building an open-source library of visualization widgets on their blockchain data.
The complex raw data is available at different levels of detail and from different viewpoints — whether we need simple aggregated transfers or parameters for failed contract calls. The support is responsive, friendly and quick.
Partnering with Bitquery has been highly cost-effective — leveraging their established infrastructure rather than building our own let us rapidly expand our blockchain support and reach a much broader segment of on-chain users.
Bitquery's products are very intuitive and easy to use. We currently use their products to obtain DEX-related trading and liquidity information, which saves us the manpower and tedious technical details required to develop our own system. Their excellent technical team deserves special praise; they provide near-24/7 support and resolve issues quickly. I greatly appreciate their products and work ethic.
Bitquery provides the infrastructure we rely on every day. Fast, reliable, and comprehensive across the chains that matter to our business.
Pricing
Start free. Scale when you ship.
Self-service plans cover 9 core chains with flat-rate add-ons — no surprise invoices. Every paid plan starts with a 7-day free trial.
Personal
For side projects, learning & testing. Personal use only — no commercial use.
billed annually ($468/yr) · save 20%
- 100k API points / mo ≈ 20k calls
- 30 req/min · 3 simultaneous
- Full GraphQL & REST schema
- Real-time data · 9 core chains 30-day window
- API only — no streams
- Community support
Pro
For trading bots, alerts & dashboards on live DEX and price data.
billed annually ($948/yr) · save 20%
- 1M API points / mo ≈ 200k calls
- 90 req/min · 6 simultaneous
- 100k stream-minutes + 5 GB
- 100 concurrent streams
- Trading-data streams live DEX & prices
- Real-time data · 9 core chains
Scale
For production real-time apps — every stream, scale on demand.
billed annually ($2,868/yr) · save 20%
- 5M API points / mo ≈ 1M calls
- 240 req/min · 12 simultaneous
- 2M stream-minutes + 50 GB
- 1,000 concurrent streams
- All streams onchain + mempool
- Dedicated Slack support
Enterprise
Full history, unlimited streams & bulk delivery at scale.
flat platform fee — no metering
- Complete history · 40+ chains
- Unlimited WebSocket streaming no stream-min or GB limit
- Custom points & rate limits
- Kafka fixed-cost · S3 bulk export
- Coinpath® money flow
- SLA · SSO · dedicated support
Flat-rate add-ons on every open plan: $40 / 1M points · $20 / 100k stream-minutes · $8 / GB (bought yearly · save 20%) — same price at any volume, billed only for what you add.
MCP server questions, answered.
What is the Bitquery MCP server?
Which clients can connect to it?
What onchain data can the agent query?
How do I set it up in Claude, Cursor or ChatGPT?
How is access authenticated and secured?
How fresh is the data?
Give your agent on-chain data this week.
Connect mcp.bitquery.io to Claude, Cursor or any MCP client and ask on-chain questions in plain English. No GraphQL, no node, no schema to teach.