On-chain market intelligence and crypto investigations for AI agents — inside Claude, ChatGPT, Cursor and VS Code.
Buttons target this host automatically — production (mcp.bitquery.io) or staging. Claude Code has no deep-link yet, so its button copies the install command to your clipboard; for ChatGPT and Codex follow the manual steps below.
📖 Full installation guide: docs.bitquery.io/docs/usecases/MCP
Every DEX trade on 8 chains, indexed down to the second — including tokens that never reach CoinGecko.
From one address to the whole story — money flows, labels, risk verdicts, flow maps.
Most crypto investigation tools cost thousands of dollars a month. Bitquery MCP does the same job inside Claude or ChatGPT: paste a wallet address, ask your question in plain English, and get the answer back — with the evidence.
In the video above we point it at a single Tron wallet and let it work: it pulls the full transaction history, labels the counterparties, tells known exchanges apart from unknown wallets, traces where the money actually moved, and writes a clear verdict — what the wallet is doing, how risky it looks, and the leads worth chasing next. The money-flow map at the end is generated in the same run.
money_flow
promptrisk_screen
promptaddress_report
promptentity_report
promptaddress_labels
— entity, category, CEX deposit / hot wallet, mixer, gambling, scam, darknet and token-clone labelsbtc_related_addresses
— common-input-ownership clusteringThese are one-shot workflows (MCP prompts/
) that chain several tools and return a chart, table or diagram. Pick them from your client's prompt / command menu:
money_flow
Trace funds from an address or transaction across hops, label counterparties, stop at exchanges / mixers → money-flow diagram + edge table.
risk_screen
AML / compliance screen of an address or transaction (mixer / sanctioned / scam / darknet) → LOW / MEDIUM / HIGH verdict + evidence + exposure diagram.
address_report
Full dossier for one address: activity stats, recent transfers, labels, and (Bitcoin) likely same-owner addresses.
entity_report
Resolve a labeled entity → its addresses → activity and connections.
The prompts are built from per-chain tracing tools your agent can also call directly — the same family exists for each traced chain (eth_
, base_
, arbitrum_
, matic_
, optimism_
, tron_
, solana_
, btc_
):
*_address_flow_summary
— one-call triage of any hop: transfer counts, top senders & receivers, and a computed role — *_flow_edges
— money-flow graph edges (source → target, amount, token), ready to render as a diagram.*_trace_next_hop
— "where did the bulk of the funds go": outgoing flow aggregated by counterparty, largest first.*_trace_dominant_path
— auto-follows the largest edge hop by hop, up to 5 hops in a single call.btc_tx_flow
— full inputs and outputs of a Bitcoin transaction with change outputs flagged, so you follow the real payment.address_labels
/ addresses_by_label
— the label directory both directions: identify one address, or pull every address tagged Investigate with FIFO, LIFO, or any methodology you prefer — the agent applies it across the raw transfer data. Transfer tracing covers:
If you work in compliance and AML, investigate fraud, or just follow the money on-chain, this gets you from an address to the whole story in about a minute.
Bitquery indexes every DEX trade on Ethereum, Arbitrum, Base, Polygon, Optimism, BNB Chain, Tron and Solana down to the second — so the answers cover freshly-launched memecoins and long-tail tokens that never appear on CoinGecko or CoinMarketCap. You ask in plain English; the agent picks the right tool:
trending_tokens
pair_ohlcv
profitable_traders_by_token
and trader_positions
trader_profile
and trader_activity
find_tokens
accumulating_traders_by_token
; profitable_traders_by_token
ranks by realized + unrealized PnL insteadtx_trades
eth_token_holders
(also Polygon, Arbitrum, Base, Optimism)execute_sql
(paid plans)token_chart
Resolve a token and render a candlestick / line price chart with a data table.
token_dashboard
360° view of one token: price chart + supply / FDV + top & smart-money traders + scam check.
trader_dashboard
One wallet: profile stats + holdings / PnL positions + activity time-series.
compare_assets
Overlay 2–5 assets on one normalized %-change price chart + stats table.
token_scout
Trending / gainers + momentum + accumulation → ranked pivot of promising tokens.
market_movers
Chain leaderboard: top gainers + most-traded → sortable table + bar chart.
arbitrage_scan
One asset across chains → price-spread % table + bar chart.
Every prompt and example above is built from individual MCP tools your agent can also call directly. The catalog groups into six families:
Discovery
find_tokens
resolves a name or ticker (with wildcards) to contract + chain; find_currencies
, token_chains
and token_dex_venues
map an asset across chains and DEXs; chain_capabilities
returns the per-chain tool matrix.
Prices & charts
token_price
/ token_ohlcv
, pair_ohlcv
(USD- or quote-denominated), cross-chain currency_*
aggregates for majors, plus supply, market cap and pool_recent_trades
. Candles from 1 second to 1 hour.
Traders
trending_tokens
(volume / gainers / losers / most-volatile), top_traders
by token, pair or network, profitable_
and accumulating_traders
, and per-wallet trader_profile
/ positions
/ activity
.
Tracing
A per-chain family for 8 chains: *_address_flow_summary
, *_flow_edges
, *_trace_next_hop
, *_trace_dominant_path
, *_transfers_in/out
, *_tx_transfers
, *_token_holders
, plus contract *_find_events
/ *_find_calls
.
Labels
address_labels
for one address, labels_for_addresses
for a batch, addresses_by_label
for every address tagged X, find_label_values
to discover what exists — entities, CEX deposit & hot wallets, mixers, gambling, scams, darknet, token clones.
Raw SQL
execute_sql
runs read-only ClickHouse over 30 days of per-second DEX trades plus the label directory; *_transfers_raw_sql
does the same on each chain's transfer data (paid plans).
The full tool list, parameter shapes, and supported networks are returned by the server itself when your client calls tools/list
— so the AI always sees the up-to-date catalog without you reading docs. Per-chain coverage varies slightly (e.g. Solana exposes solana_find_instructions
, Bitcoin adds btc_related_addresses
clustering); chain_capabilities
is the authoritative matrix.
The underlying dataset is the same Bitquery you already know. The difference is the interface:
Install Bitquery as a custom connector in your AI client. No config file editing required. Watch the walkthrough:
https://mcp.bitquery.io
Add Bitquery to Claude Code with one command (the Add to Claude Code button above copies it to your clipboard):
claude mcp add --transport http bitquery https://mcp.bitquery.io
Append --scope user
to enable it across every project. On first use, run /mcp
inside Claude Code (or claude mcp login bitquery
) and complete the browser OAuth login with your Bitquery account.
https://mcp.bitquery.io
https://mcp.bitquery.io
Add Bitquery to your Codex MCP servers with the CLI:
codex mcp add bitquery --url https://mcp.bitquery.io
Or edit ~/.codex/config.toml
directly:
[mcp_servers.bitquery]
url = "https://mcp.bitquery.io"
On first call, Codex opens a browser for OAuth login with your Bitquery account.
Add a new MCP server with URL: https://mcp.bitquery.io
It is a hosted Model Context Protocol (MCP) server at https://mcp.bitquery.io
that exposes Bitquery's on-chain blockchain data as MCP tools. AI agents like Claude, ChatGPT, Cursor, and VS Code can call these tools directly during a conversation, without you having to write GraphQL queries by hand.
Yes. The server ships guided investigation prompts: money_flow
traces funds across hops and stops at exchanges or mixers, risk_screen
returns a LOW / MEDIUM / HIGH AML verdict with evidence, address_report
builds a full dossier for one address, and entity_report
resolves a labeled entity to its addresses and activity. Transfer tracing covers Ethereum, Polygon, Arbitrum, Base, Optimism, Tron, Bitcoin and Solana, backed by millions of address labels.
Any client that supports remote MCP servers over Streamable HTTP. This includes Claude Desktop and Claude.ai (web, with Plus/Pro/Max), ChatGPT (Plus/Pro/Business with custom connectors enabled), Cursor, VS Code with MCP enabled, and custom agents built with the Anthropic or OpenAI SDKs.
DEX trading tools cover Ethereum, Arbitrum, Base, Polygon, Optimism, BNB Chain, Tron and Solana, with candles down to 1-second granularity; transfer-tracing tools cover Ethereum, Polygon, Arbitrum, Base, Optimism, Tron, Bitcoin and Solana. Tools span token prices, OHLCV candles, trending tokens, top / profitable / accumulating traders, trader profiles and positions, DEX pairs, transfers, the address-label directory, and raw SQL access where the user has a paid plan.
Authentication uses OAuth 2.1: the AI client opens a browser to your Bitquery account, you approve access, and tokens refresh automatically for ~30 days. Access is tied to your Bitquery account, so revoking it there immediately disables the connection.
The MCP server is built for AI agents. Instead of writing a GraphQL query, the agent picks an MCP tool (for example token_ohlcv
or top_traders_by_token
) and the server runs the underlying query on Bitquery for you. The data source is the same; the interface is conversational. Quotas, plans, and billing are shared with your regular Bitquery account.
There is a free tier inherited from your Bitquery account. Heavier workloads — high request rates, large historical scans, or execute_sql
— require a paid Bitquery plan. The MCP server itself does not add a separate charge.