# MCP to Talk to Blockchain Data > Source: > Published: 2026-08-26 09:17:01+00:00 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](https://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` prompt`risk_screen` prompt`address_report` prompt`entity_report` prompt`address_labels` — entity, category, CEX deposit / hot wallet, mixer, gambling, scam, darknet and token-clone labels`btc_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 instead`tx_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.