Bitquery MCP. Query any blockchain, live or historical, in one API call.
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Bitquery (Web3 Blockchain GraphQL APIs) connects your AI agent to live and historical blockchain data across 40+ chains. Use GraphQL queries to analyze transactions, track DeFi activity, or audit smart contracts on Bitcoin, Ethereum, Solana, and more.
Generate OAuth2 tokens and execute complex queries with a single API call.
What your AI agents can do
Generate token
Generates an OAuth2 access token using your Client ID and Secret, which must be used for subsequent queries.
Query v1
Executes a GraphQL query against the V1 Historical API to retrieve long-term blockchain data across 40+ chains.
Query v2
Executes an advanced GraphQL query against the V2 Streaming API, supporting complex joins and real-time data streams.
Runs the generate_token tool to issue an OAuth2 access token, which your agent then uses for all subsequent queries.
Uses query_v1 to execute a standard GraphQL query against the V1 Historical API, retrieving data for long-term analysis.
Executes query_v2 to run advanced GraphQL queries against the V2 Streaming API, enabling monitoring of live events and complex joins.
Runs specialized queries against cubes like DexTrades to calculate liquidity and track token performance across major DeFi protocols.
Analyzes specific contract data—like Calls and Events—to understand exactly how protocols interact on-chain.
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Bitquery (Web3 Blockchain GraphQL APIs) MCP Server: 3 Tools
Use these three tools to authenticate, query historical data, or stream live blockchain events across multiple chains via GraphQL.
019e5cffgenerate token
Generates an OAuth2 access token using your Client ID and Secret, which must be used for subsequent queries.
019e5cffquery v1
Executes a GraphQL query against the V1 Historical API to retrieve long-term blockchain data across 40+ chains.
019e5cffquery v2
Executes an advanced GraphQL query against the V2 Streaming API, supporting complex joins and real-time data streams.
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What you can do with this MCP connector
Bitquery connects your AI agent to live and historical blockchain data across 40+ chains. You'll use GraphQL queries to analyze transactions, track DeFi activity, or audit smart contracts on Bitcoin, Ethereum, Solana, and more. First, you've gotta run generate_token to get an OAuth2 access token using your Client ID and Secret; your agent needs that token for all the queries that follow.
To look at long-term blockchain data, you'll use query_v1, which executes a standard GraphQL query against the V1 Historical API, giving you data for long-term analysis across 40+ chains.
For real-time monitoring, you'll hit up query_v2. This runs an advanced GraphQL query against the V2 Streaming API, letting you monitor live events and complex joins. You can analyze decentralized exchange trades by running specialized queries against cubes like DexTrades to calculate liquidity and track token performance across major DeFi protocols.
You can also inspect smart contract interactions by analyzing specific contract data—like Calls and Events—to figure out exactly how protocols talk on-chain.
How Bitquery MCP Works
- 1 First, run
generate_tokenusing your Client ID and Secret to get a valid OAuth2 access token. - 2 Next, provide the desired data structure (a GraphQL query) and specify which version of data you need (V1 for history, V2 for live stream).
- 3 Your agent executes the query using
query_v1orquery_v2with the token, and you get structured data representing the requested blockchain events or transactions.
The bottom line is: you pass your credentials once, and your agent can then execute complex, multi-chain data retrieval queries using a single unified interface.
Who Is Bitquery MCP For?
Web3 Developers, Data Analysts, and Security Researchers. If your job involves tracking asset movements, auditing smart contracts, or building anything on-chain, you need this. It’s for anyone whose workflow gets blocked by having to jump between multiple blockchain explorers or API dashboards.
Uses the server to debug smart contract calls or verify on-chain events directly from their IDE, integrating complex data into their application logic.
Performs cross-chain analysis and extracts market metrics—like total liquidity or trading volume—by querying specialized cubes like DexTrades.
Audits historical transactions and tracks fund movements across multiple protocols to identify potential vulnerabilities or suspicious activity.
What Changes When You Connect
- Real-time monitoring of events: Use
query_v2to access live data for EVM-compatible chains and Solana. You can monitor transfers, smart contract calls, and events as they happen, eliminating the need to refresh multiple explorer pages. - Cross-chain data visibility: Query historical data across 40+ chains—Bitcoin, Polygon, Ethereum, etc.—with
query_v1. This lets you run single analysis reports that cover assets across dozens of ecosystems. - Deep DeFi metrics: Specialized cubes like
DexTradeslet you track liquidity and token performance. You don't have to stitch together data from Uniswap, Curve, and other DEXs; you get it all in one query. - Efficient authentication: Running
generate_tokenhandles the OAuth2 process. Your agent gets a single, usable token, so you don't have to manage credentials or worry about separate API keys for every chain. - Smart contract analysis: You can analyze
Calls,Events, andInstructionsdirectly. This means you can understand the exact protocol interaction behind a transaction without manually decoding the raw logs.
Real-World Use Cases
Tracking a large fund movement
A security researcher needs to audit a large fund movement across multiple protocols. They ask their agent to use query_v1 to check historical data across Bitcoin and Polygon. The agent successfully retrieves all associated transactions, providing a complete, time-stamped movement map that was impossible to build by manually checking separate explorers.
Monitoring a live NFT mint
A developer is launching an NFT mint and needs to track every sale in real time. They instruct their agent to use query_v2 on an EVM-compatible chain. The agent streams live data, allowing the developer to see every transfer and smart contract call as it happens, confirming the mint's live activity.
Calculating total market liquidity
A DeFi analyst wants to know the total liquidity across three major DEXs. Instead of running three separate reports, they ask their agent to use query_v2 with the specialized DexTrades cube. The agent returns a unified data set, instantly calculating the overall market depth.
Debugging a failed protocol call
A developer runs into a bug where a smart contract call fails. They tell their agent to use query_v2 to inspect the Calls and Events data. The agent pulls the necessary protocol interaction logs, allowing the developer to pinpoint the exact line of code causing the failure.
The Tradeoffs
Using separate API endpoints
Trying to query Bitcoin history using one API, and then querying Ethereum history using a completely different API service. This requires managing two separate sets of credentials and two different query structures.
→
Use generate_token first to get one token. Then, use query_v1 or query_v2 to execute a single GraphQL query that spans both Bitcoin and Ethereum data. The whole process stays within one API call.
Ignoring versioning (V1 vs V2)
Running a simple query that only retrieves the last 10 blocks using query_v1, when what you actually need is the live stream of transfers. The data you get is static and misses all the current activity.
→
If you need to monitor what's happening right now, use query_v2. This tool handles advanced joins and streaming, giving you the real-time data you need, not just a historical snapshot.
Hardcoding credentials
Embedding your Client ID and Secret directly into your script or prompt. This is a massive security risk and requires manual rotation every time your keys change.
→
Always start by calling generate_token. Use the resulting Bearer token in your subsequent calls to query_v1 or query_v2. This keeps your sensitive credentials out of the operational code.
When It Fits, When It Doesn't
Use this server if your goal is to analyze, audit, or build anything on-chain. You need to query data across multiple chains (e.g., Bitcoin and Polygon) or if you need both historical records and live, streaming events. You must use this if your workflow requires understanding the relationship between data points (e.g., tracking a token from a DEX trade to a smart contract call).
Don't use this if you only need simple, single-source data—like checking a single address's balance on one chain. For that, a simpler, dedicated endpoint might suffice. But if the data needs to be combined or analyzed across chains, Bitquery is the only way to go.
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Bitquery. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
VINKIUS INFRASTRUCTURE
Cloud Hosted
Managed infra
V8 Isolated
Sandboxed per request
Zero-Trust Proxy
No stored credentials
DLP Enforced
Policy on every call
GDPR Compliant
EU data residency
Token Compression
~60% cost reduction
Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This server provides 3 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Available Capabilities
Analyzing on-chain data used to require jumping between five different web explorers.
Today, checking a fund movement is a manual mess. You have to open the Bitcoin explorer, check the transaction hash; then open the Polygon explorer to see the bridge transaction; then maybe open a DeFi dashboard to see the initial token buy-in. You spend 20 minutes just copying and pasting hashes and cross-referencing dates.
With this MCP server, you ask your agent to map the movement. It runs the necessary queries using `query_v1` and pulls the complete history—from the initial Bitcoin transfer to the final Polygon event—and gives you a single, structured answer. You stop copy-pasting and start analyzing.
Bitquery (Web3 Blockchain GraphQL APIs) MCP Server: Stream live, complex data.
Before, if you wanted to watch a token sale, you'd have to refresh the page every few seconds, hoping you didn't miss a critical trade. You were always seconds behind the actual activity, and you couldn't even track related events like the smart contract calls that followed the sale.
Now, use `query_v2`. It streams the live data. You get the trade, the transfer, and the resulting contract call all at once, instantly. It's not a snapshot; it's the full, continuous record.
Common Questions About Bitquery MCP
How do I use the generate_token tool with Bitquery (Web3 Blockchain GraphQL APIs)? +
You run generate_token with your Client ID and Secret. The tool returns a Bearer token that you must use for all subsequent queries with query_v1 or query_v2.
What's the difference between query_v1 and query_v2 in the Bitquery (Web3 Blockchain GraphQL APIs) MCP Server? +
query_v1 is for historical data (V1) and is great for auditing old records. query_v2 handles real-time streaming and complex joins (V2), which is necessary for monitoring live activity.
Can I query data from multiple blockchains using query_v1? +
Yes. The server supports cross-chain querying. You can use query_v1 to get historical data from Bitcoin, Ethereum, Polygon, and many others in one request.
How do I query DeFi trades using the Bitquery (Web3 Blockchain GraphQL APIs) MCP Server? +
Use query_v2 and reference specialized cubes like DexTrades. These cubes are designed to calculate and retrieve DeFi market metrics, simplifying complex liquidity tracking.
How do I manage my connection credentials using the generate_token tool in the Bitquery (Web3 Blockchain GraphQL APIs) MCP Server? +
You generate an OAuth2 access token using generate_token with your Client ID and Secret. This token must be used as the BITQUERY_ACCESS_TOKEN credential for all subsequent queries.
What kind of data can I analyze for historical trends using the query_v1 tool? +
query_v1 handles historical data across 40+ chains, including Bitcoin, Polygon, and Tron. You can audit past transactions or track long-term trends for specific assets.
Do I need to worry about real-time data limits when using the query_v2 tool? +
The query_v2 tool supports real-time streaming for EVM-compatible chains and Solana. For high-volume monitoring, check the provider's documentation for rate limit guidelines.
Can the query_v2 tool handle complex DeFi analytics like tracking liquidity? +
Yes, query_v2 provides specialized cubes like DexTrades and DexTradesByTokens. These let you track liquidity, trades, and token performance programmatically.
What is the difference between query_v1 and query_v2? +
Use query_v1 for historical data across 40+ legacy and non-EVM chains (like Bitcoin). Use query_v2 for real-time streaming and advanced filtering on EVM chains and Solana, supporting complex joins like 'joinCalls'.
How do I obtain an access token if I only have a Client ID and Secret? +
You can use the generate_token tool. Provide your Bitquery Client ID and Secret, and the tool will return a Bearer token that you can use as your BITQUERY_ACCESS_TOKEN credential.
Can I query data from multiple regions? +
Yes. Both query_v1 and query_v2 support an optional region parameter. You can choose between 'global', 'asia', or 'us' to optimize latency based on your location.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
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