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BlockRunAI

BlockRun MCP

Official
by BlockRunAI

blockrun_wallet

Manage payment wallets, check USDC balances, set spending limits, and delegate budgets to child agents across Base and Solana chains.

Instructions

Call this tool to manage the BlockRun payment wallet and control agent spending budgets.

Call this FIRST if any other blockrun_* tool returns a payment/balance error. Call this to check your current USDC balance before expensive operations. Call this to set spending limits before spawning child agents.

The server holds TWO wallets — one on Base, one on Solana — but pays on ONE active chain at a time. status shows both addresses/balances and which is active. Default chain is Base.

To pay on Solana (no env vars, no file editing, no restart):

  1. action:"chain" chain:"solana" → provisions + activates the Solana wallet

  2. action:"setup" → Solana address + funding QR (send USDC SPL on Solana) Switch back with action:"chain" chain:"base". Base-only — these ignore Solana and need Base: blockrun_image, blockrun_music, blockrun_speech, blockrun_video, paid blockrun_price, blockrun_chat routing:"smart", and native Anthropic (claude-*).

Actions:

  • status (default): Both wallet addresses + USDC balances, active chain, session spending

  • setup: Get funding instructions + QR code for the ACTIVE chain (call this when balance is 0)

  • qr: Open QR code (active chain) in system viewer

  • chain + chain:"base"|"solana": Switch the active payment chain (omit chain: to just see the current one)

Budget controls:

  • budget + budget_action:"set" + budget_amount:1.00 → Set global spend cap

  • budget + budget_action:"clear" → Remove global spend cap

Multi-agent orchestration:

  • delegate + agent_id:"research" + agent_limit:2.00 → Allocate $2 to a child agent

  • revoke + agent_id:"research" → Remove a child agent's budget

  • report → See per-agent spending breakdown

Usage pattern for multi-agent systems:

  1. blockrun_wallet action:"delegate" agent_id:"worker-1" agent_limit:1.00

  2. Pass agent_id:"worker-1" to all blockrun_chat/search/etc calls for that agent

  3. blockrun_wallet action:"report" to audit spending

Do NOT call this for actual AI queries — use blockrun_chat for that.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actionNoWhat to dostatus
chainNoTarget chain for action='chain'. Omit to view the current active chain.
budget_actionNoBudget action (for action='budget')
budget_amountNoBudget limit in USD (for budget_action='set')
agent_idNoAgent identifier for delegate/revoke/report actions
agent_limitNoBudget limit in USD for this agent (required for delegate action)
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It thoroughly explains the tool's behavior: two wallets on Base and Solana, active chain switching without env vars, actions' effects (e.g., 'provisions + activates the Solana wallet'), budget controls, and multi-agent orchestration. All behavioral traits are disclosed.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is thorough and well-structured with bullet points for actions, budget controls, and usage patterns. While it is longer than necessary, every sentence contributes value. It is front-loaded with the most critical usage guidance ('Call this FIRST...'). A slight trim could improve conciseness, but it remains effective.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, so the description should explain return values. It does so partially: 'status shows both addresses/balances and which is active', 'report → See per-agent spending breakdown', 'setup: Get funding instructions + QR code'. However, it does not describe the exact format or structure of responses for actions like budget or delegate. Given the complexity of the tool, a bit more detail would be beneficial, but it is largely complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 6 parameters with 100% description coverage, but the description adds extensive meaning: it explains each action in detail (status, setup, QR, chain, budget, delegate, revoke, report), provides examples (e.g., budget_action:'set' with budget_amount:1.00), and clarifies parameter interplay (e.g., agent_id required for delegate/revoke). The description transforms bare schema into usable knowledge.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly specifies the action: 'manage the BlockRun payment wallet and control agent spending budgets'. It explicitly differentiates from sibling tools by stating 'Do NOT call this for actual AI queries — use blockrun_chat for that.' The verb-resource combination is specific and unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit when-to-use guidance: 'Call this FIRST if any other blockrun_* tool returns a payment/balance error', 'Call this to check your current USDC balance before expensive operations', and 'Call this to set spending limits before spawning child agents.' It also tells when not to use and offers an alternative tool (blockrun_chat). A multi-agent usage pattern is provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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