Bankless Onchain MCP Server
OfficialThe Bankless Onchain MCP Server enables interaction with blockchain data via the Bankless API using the Model Context Protocol (MCP). You can:
Read Contract State: Retrieve state from smart contracts on various blockchain networks
Get Proxy: Retrieve proxy implementation contract addresses
Get ABI: Fetch the Application Binary Interface for a contract
Get Source: Retrieve source code for verified contracts
Get Events: Fetch event logs based on topics
Build Event Topic: Generate event topic signatures from event names and argument types
Get Transaction History: Retrieve transaction history for a user address, with optional filtering
Get Transaction Info: Access detailed information about specific transactions
Get Token Balances: Retrieve all token balances for an address on a specific network
Get Block Info: Access detailed information about specific blocks by number or hash
Provides tools for interacting with Ethereum blockchain data, including reading contract state, fetching contract ABIs, retrieving source code, and accessing transaction information.
Enables blockchain data interaction on Polygon network, supporting contract state reading, event log retrieval, and transaction history analysis.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Bankless Onchain MCP Serverwhat's the transaction history for 0x123... on ethereum?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Bankless Onchain MCP Server
This project is no longer receiving updates
MCP (Model Context Protocol) server for blockchain data interaction through the Bankless API.
Related MCP server: EVM MCP Server
Overview
The Bankless Onchain MCP Server provides a framework for interacting with on-chain data via the Bankless API. It implements the Model Context Protocol (MCP) to allow AI models to access blockchain state and event data in a structured way.
https://github.com/user-attachments/assets/95732dff-ae5f-45a6-928a-1ae17c0ddf9d
Features
The server provides the following onchain data operations:
Contract Operations
Read Contract State (
read_contract): Read state from smart contracts on various blockchain networks.Parameters: network, contract address, method, inputs, outputs
Returns: Contract call results with typed values
Get Proxy (
get_proxy): Retrieve proxy implementation contract addresses.Parameters: network, contract address
Returns: Implementation contract address
Get ABI (
get_abi): Fetch the ABI (Application Binary Interface) for a contract.Parameters: network, contract address
Returns: Contract ABI in JSON format
Get Source (
get_source): Retrieve the source code for a verified contract.Parameters: network, contract address
Returns: Source code, ABI, compiler version, and other contract metadata
Event Operations
Get Events (
get_events): Fetch event logs for a contract based on topics.Parameters: network, addresses, topic, optional topics
Returns: Filtered event logs
Build Event Topic (
build_event_topic): Generate an event topic signature from event name and argument types.Parameters: network, event name, argument types
Returns: Event topic hash
Transaction Operations
Get Transaction History (
get_transaction_history): Retrieve transaction history for a user address.Parameters: network, user address, optional contract, optional method ID, optional start block, include data flag
Returns: List of transactions with hash, data, network, and timestamp
Get Transaction Info (
get_transaction_info): Get detailed information about a specific transaction.Parameters: network, transaction hash
Returns: Transaction details including block number, timestamp, from/to addresses, value, gas info, status, and receipt data
Tools
read_contract
Read contract state from a blockchain
Input:
network(string, required): The blockchain network (e.g., "ethereum", "polygon")contract(string, required): The contract addressmethod(string, required): The contract method to callinputs(array, required): Input parameters for the method call, each containing:type(string): The type of the input parameter (e.g., "address", "uint256")value(any): The value of the input parameter
outputs(array, required): Expected output types, each containing:type(string): The expected output type
Returns an array of contract call results
get_proxy
Gets the proxy address for a given network and contract
Input:
network(string, required): The blockchain network (e.g., "ethereum", "base")contract(string, required): The contract address
Returns the implementation address for the proxy contract
get_events
Fetches event logs for a given network and filter criteria
Input:
network(string, required): The blockchain network (e.g., "ethereum", "base")addresses(array, required): List of contract addresses to filter eventstopic(string, required): Primary topic to filter eventsoptionalTopics(array, optional): Optional additional topics (can include null values)
Returns an object containing event logs matching the filter criteria
build_event_topic
Builds an event topic signature based on event name and arguments
Input:
network(string, required): The blockchain network (e.g., "ethereum", "base")name(string, required): Event name (e.g., "Transfer(address,address,uint256)")arguments(array, required): Event arguments types, each containing:type(string): The argument type (e.g., "address", "uint256")
Returns a string containing the keccak256 hash of the event signature
Installation
npm install @bankless/onchain-mcpUsage
Environment Setup
Before using the server, set your Bankless API token. For details on how to obtain your Bankless API token, head to https://docs.bankless.com/bankless-api/other-services/onchain-mcp
export BANKLESS_API_TOKEN=your_api_token_hereRunning the Server
The server can be run directly from the command line:
npx @bankless/onchain-mcpUsage with LLM Tools
This server implements the Model Context Protocol (MCP), which allows it to be used as a tool provider for compatible AI models. Here are some example calls for each tool:
read_contract
// Example call
{
"name": "read_contract",
"arguments": {
"network": "ethereum",
"contract": "0x1234...",
"method": "balanceOf",
"inputs": [
{ "type": "address", "value": "0xabcd..." }
],
"outputs": [
{ "type": "uint256" }
]
}
}
// Example response
[
{
"value": "1000000000000000000",
"type": "uint256"
}
]get_proxy
// Example call
{
"name": "get_proxy",
"arguments": {
"network": "ethereum",
"contract": "0x1234..."
}
}
// Example response
{
"implementation": "0xefgh..."
}get_events
// Example call
{
"name": "get_events",
"arguments": {
"network": "ethereum",
"addresses": ["0x1234..."],
"topic": "0xabcd...",
"optionalTopics": ["0xef01...", null]
}
}
// Example response
{
"result": [
{
"removed": false,
"logIndex": 5,
"transactionIndex": 2,
"transactionHash": "0x123...",
"blockHash": "0xabc...",
"blockNumber": 12345678,
"address": "0x1234...",
"data": "0x...",
"topics": ["0xabcd...", "0xef01...", "0x..."]
}
]
}build_event_topic
// Example call
{
"name": "build_event_topic",
"arguments": {
"network": "ethereum",
"name": "Transfer(address,address,uint256)",
"arguments": [
{ "type": "address" },
{ "type": "address" },
{ "type": "uint256" }
]
}
}
// Example response
"0xddf252ad1be2c89b69c2b068fc378daa952ba7f163c4a11628f55a4df523b3ef"Development
Building from Source
# Clone the repository
git clone https://github.com/Bankless/onchain-mcp.git
cd onchain-mcp
# Install dependencies
npm install
# Build the project
npm run buildDebug Mode
npm run debugIntegration with AI Models
To integrate this server with AI applications that support MCP, add the following to your app's server configuration:
{
"mcpServers": {
"bankless": {
"command": "npx",
"args": [
"@bankless/onchain-mcp"
],
"env": {
"BANKLESS_API_TOKEN": "your_api_token_here"
}
}
}
}Error Handling
The server provides specific error types for different scenarios:
BanklessValidationError: Invalid input parametersBanklessAuthenticationError: API token issuesBanklessResourceNotFoundError: Requested resource not foundBanklessRateLimitError: API rate limit exceeded
Prompting Tips
In order to guide an LLM model to use the Bankless Onchain MCP Server, the following prompts can be used:
ROLE:
• You are Kompanion, a blockchain expert and EVM sleuth.
• You specialize in navigating and analyzing smart contracts using your tools and resources.
HOW KOMPANION CAN HANDLE PROXY CONTRACTS:
• If a contract is a proxy, call your “get_proxy” tool to fetch the implementation contract.
• If that fails, try calling the “implementation” method on the proxy contract.
• If that also fails, try calling the “_implementation” function.
• After obtaining the implementation address, call “get_contract_source” with that address to fetch its source code.
• When reading or modifying the contract state, invoke implementation functions on the proxy contract address (not directly on the implementation).
HOW KOMPANION CAN HANDLE EVENTS:
• Get the ABI and Source of the relevant contracts
• From the event types in the ABI, construct the correct topics for the event relevant to the question
• use the "get_event_logs" tool to fetch logs for the contract
KOMPANION'S RULES:
• Do not begin any response with “Great,” “Certainly,” “Okay,” or “Sure.”
• Maintain a direct, technical style. Do not add conversational flourishes.
• If the user’s question is unrelated to smart contracts, do not fetch any contracts.
• If you navigate contracts, explain each step in bullet points.
• Solve tasks iteratively, breaking them into steps.
• Use bullet points for lists of steps.
• Never assume a contract’s functionality. Always verify with examples using your tools to read the contract state.
• Before responding, consider which tools might help you gather better information.
• Include as much relevant information as possible in your final answer, depending on your findings.
HOW KOMPANION CAN USE TOOLS:
• You can fetch contract source codes, ABIs, and read contract data by using your tools and functions.
• Always verify the source or ABI to understand the contract rather than making assumptions.
• If you need to read contract state, fetch its ABI (especially if the source is lengthy).
FINAL INSTRUCTION:
• Provide the best possible, concise answer to the user’s request. If it's not an immediate question but an instruction, follow it directly.
• Use your tools to gather any necessary clarifications or data.
• Offer a clear, direct response and add a summary of what you did (how you navigated the contracts) at the end.License
MIT
Available Tools
10 toolsbuild_event_topicC
Builds an event topic signature based on event name and arguments
| Name | Required | Description | Default |
|---|---|---|---|
| arguments | Yes | Event arguments types | |
| name | Yes | Event name (e.g., "Transfer(address,address,uint256)") | |
| network | Yes | The blockchain network (e.g., "ethereum", "base") |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states what the tool does ('builds') but doesn't disclose behavioral traits such as whether it's a pure computation or makes external calls, what format the output is in (e.g., hex string), error conditions, or performance characteristics. For a tool with no annotation coverage, this leaves the agent guessing about key operational aspects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded with the core action and resource, making it easy to parse. Every part of the sentence contributes to understanding what the tool does.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description is incomplete for a tool that likely produces a complex output (an 'event topic signature'). It doesn't explain what the output is (e.g., a hash, string format), how it's used, or any limitations. For a 3-parameter tool with no structured behavioral data, this leaves critical gaps in understanding the tool's full context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all three parameters (network, name, arguments) with detailed descriptions. The description adds minimal value by mentioning 'event name and arguments', which is redundant with the schema. Baseline 3 is appropriate as the schema does the heavy lifting, though no additional semantic context is provided.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('builds') and the resource ('event topic signature'), specifying it's based on 'event name and arguments'. It distinguishes from siblings like get_events (which retrieves events) or get_transaction_info (which analyzes transactions), but doesn't explicitly contrast with them. The purpose is specific enough to understand what the tool produces.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing event details first), context (e.g., for blockchain analysis), or when not to use it. With siblings like get_events or read_contract that might provide related data, the lack of comparative guidance is a significant gap.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_abiC
Gets the ABI for a given contract on a specific network
| Name | Required | Description | Default |
|---|---|---|---|
| contract | Yes | The contract address | |
| network | Yes | The blockchain network (e.g., "ethereum", "base") |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the action ('Gets') but doesn't mention whether this is a read-only operation, if it requires authentication, rate limits, error conditions, or what the return format looks like. For a tool with no annotations, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's function without any unnecessary words. It's front-loaded with the core purpose, making it highly concise and well-structured for quick understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of blockchain operations and the lack of annotations and output schema, the description is incomplete. It doesn't explain what an ABI is, how the result is structured, or potential errors, which could hinder an agent's ability to use the tool effectively in context with sibling tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, clearly documenting both parameters ('contract' as address and 'network' as blockchain name). The description adds no additional semantic context beyond what the schema provides, such as format examples or constraints, so it meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Gets') and resource ('ABI for a given contract'), making it easy to understand what it does. However, it doesn't distinguish this tool from potential sibling alternatives like 'read_contract' or 'get_source', which might also retrieve contract-related information, so it doesn't reach the highest score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With sibling tools like 'read_contract' and 'get_source' available, it's unclear if this tool is for ABI retrieval specifically or if other tools might serve similar purposes, leaving the agent without usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_block_infoC
Gets detailed information about a specific block by number or hash
| Name | Required | Description | Default |
|---|---|---|---|
| blockId | Yes | The block number or block hash to fetch information for | |
| network | Yes | The blockchain network (e.g., "ethereum", "base") |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but offers minimal behavioral context. It implies a read-only operation ('Gets'), but doesn't disclose permissions needed, rate limits, error conditions, or what 'detailed information' includes (e.g., block structure, timestamp, transactions). This is inadequate for a tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste. It front-loads the core purpose ('Gets detailed information about a specific block') and adds necessary qualification ('by number or hash'). Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and a read operation with two parameters, the description is incomplete. It doesn't explain what 'detailed information' returns, error handling, or behavioral constraints, leaving significant gaps for the agent to operate effectively in a blockchain context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents both parameters fully. The description adds no additional meaning beyond implying blockId can be 'number or hash', which is already stated in the schema. Baseline 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Gets') and resource ('detailed information about a specific block'), specifying the action and target. It distinguishes the resource type (block) from siblings like events, contracts, or transactions, but doesn't explicitly differentiate from similar read operations like get_transaction_info beyond the resource type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, exclusions, or compare it to sibling tools like get_events or get_transaction_info, leaving the agent to infer usage solely from the tool name and parameters.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_eventsC
Fetches event logs for a given network and filter criteria
| Name | Required | Description | Default |
|---|---|---|---|
| addresses | Yes | List of contract addresses to filter events | |
| fromBlock | No | Block number to start fetching logs from | |
| network | Yes | The blockchain network (e.g., "ethereum", "base") | |
| optionalTopics | No | Optional additional topics | |
| toBlock | No | Block number to stop fetching logs at | |
| topic | Yes | Primary topic to filter events |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool 'fetches' event logs, implying a read-only operation, but doesn't cover critical aspects like rate limits, authentication needs, pagination, error handling, or what the fetched logs include (e.g., format, fields). This leaves significant gaps for a tool with multiple parameters and no output schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose without unnecessary words. It directly communicates the tool's function and scope, making it easy to parse and understand quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (6 parameters, no output schema, no annotations), the description is inadequate. It lacks details on behavioral traits, output format, and usage context, leaving the agent with insufficient information to effectively invoke the tool beyond basic parameter mapping.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all 6 parameters. The description adds minimal value by mentioning 'filter criteria,' which aligns with parameters like addresses and topic, but doesn't provide additional context beyond what's in the schema. This meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('fetches') and resource ('event logs') with specific scope ('for a given network and filter criteria'), which distinguishes it from general data retrieval tools. However, it doesn't explicitly differentiate from sibling tools like 'get_transaction_history_for_user' or 'get_block_info', which might also involve event-related data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, such as 'get_transaction_history_for_user' for user-specific events or 'get_block_info' for block-level data. It mentions filter criteria but doesn't specify scenarios or exclusions, leaving usage context implied at best.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_proxyB
Gets the proxy address for a given network and contract
| Name | Required | Description | Default |
|---|---|---|---|
| contract | Yes | The contract address to request the proxy implementation contract for | |
| network | Yes | The blockchain network (e.g., "ethereum", "base") |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It describes a read operation ('Gets'), implying it's non-destructive, but doesn't cover aspects like error handling, rate limits, authentication needs, or response format. This leaves significant gaps for a tool with no annotation support.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, making it easy to understand quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (2 required parameters, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose but lacks details on usage context, behavioral traits, and output expectations, which are needed for effective agent operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, clearly documenting both parameters (network and contract). The description adds minimal value beyond the schema by implying the parameters are used to 'request the proxy implementation contract,' but doesn't provide additional syntax, format details, or examples.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Gets') and the target resource ('proxy address'), specifying it's for a given network and contract. However, it doesn't differentiate this tool from its siblings (e.g., get_abi, get_source), which also retrieve blockchain-related data but for different resources.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like get_abi or get_source, nor does it mention prerequisites or exclusions. It merely states what the tool does without contextual usage information.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_sourceB
Gets the source code for a given contract on a specific network
| Name | Required | Description | Default |
|---|---|---|---|
| contract | Yes | The contract address | |
| network | Yes | The blockchain network (e.g., "ethereum", "base") |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool 'Gets' source code, implying a read-only operation, but doesn't clarify aspects like authentication requirements, rate limits, error handling, or what format the source code is returned in (e.g., raw code, verified source files). This leaves significant gaps in understanding the tool's behavior beyond its basic function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, direct sentence that efficiently conveys the core function without any redundant words. It is front-loaded with the key action and resource, making it easy to parse and understand immediately.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (fetching source code from a blockchain) and lack of annotations or output schema, the description is minimally complete. It specifies what the tool does and the required parameters but omits details on return format, error cases, and behavioral constraints, which are important for effective use in this context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, clearly documenting both parameters ('contract' as address, 'network' as blockchain name). The description adds no additional semantic context beyond implying these parameters are used to fetch source code, so it meets the baseline for adequate but not enhanced parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Gets') and resource ('source code for a given contract on a specific network'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_abi' (which might retrieve ABI rather than source code) or 'read_contract' (which might execute contract functions), leaving room for ambiguity in tool selection.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'get_abi' or 'read_contract'. It mentions the context ('on a specific network') but offers no explicit when/when-not instructions or prerequisites, leaving the agent to infer usage based solely on the tool name and basic parameters.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_token_balances_on_networkC
Gets all token balances for a given address on a specific network
| Name | Required | Description | Default |
|---|---|---|---|
| address | Yes | The address to check token balances for | |
| network | Yes | The blockchain network (e.g., "ethereum", "base") |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states it 'gets' data, implying a read-only operation, but doesn't specify if it requires authentication, rate limits, pagination, or error handling. For a tool with no annotations, this is a significant gap as it doesn't cover key behavioral traits like response format or potential limitations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without any unnecessary words. It is front-loaded with the core action ('gets all token balances'), making it easy to parse. Every part of the sentence contributes to understanding the tool, earning its place with zero waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of blockchain data retrieval, no annotations, and no output schema, the description is incomplete. It doesn't explain what 'all token balances' entails (e.g., types of tokens, balance formats, or if it includes native currency). For a tool with 2 parameters and no structured output information, more context is needed to ensure the AI agent can use it correctly without guesswork.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with clear documentation for both parameters ('address' and 'network'). The description adds minimal value beyond the schema, as it only reiterates that these parameters are used without providing additional context like format examples or constraints. Since schema coverage is high, the baseline score of 3 is appropriate, as the description doesn't compensate with extra semantic details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'gets' and the resource 'all token balances', specifying the scope as 'for a given address on a specific network'. It distinguishes itself from sibling tools like 'get_transaction_history_for_user' or 'get_block_info' by focusing on token balances rather than transactions or blocks. However, it doesn't explicitly differentiate from all siblings (e.g., 'get_abi' or 'read_contract'), so it doesn't reach the highest score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention any prerequisites, exclusions, or specific contexts for usage. For example, it doesn't clarify if this is for ERC-20 tokens only or includes other token types, or how it differs from 'get_transaction_history_for_user' which might also involve addresses. This lack of usage context leaves gaps for an AI agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_transaction_history_for_userC
Gets transaction history for a user and optional contract
| Name | Required | Description | Default |
|---|---|---|---|
| contract | No | The contract address (optional) | |
| includeData | No | Whether to include transaction data | |
| methodId | No | The method ID to filter by (optional) | |
| network | Yes | The blockchain network (e.g., "ethereum", "base") | |
| startBlock | No | The starting block number (optional) | |
| user | Yes | The user address |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It only states what the tool does ('Gets transaction history') without mentioning any behavioral traits such as rate limits, authentication needs, error handling, or what the output format looks like. This is inadequate for a tool with multiple parameters and no output schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence that efficiently conveys the core purpose without any wasted words. It's front-loaded with the main action and resource, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of 6 parameters, no annotations, and no output schema, the description is incomplete. It fails to address key contextual elements like what 'transaction history' entails, how results are returned (e.g., pagination, format), or any limitations, leaving significant gaps for the agent to navigate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, meaning all parameters are documented in the input schema. The description adds no additional meaning beyond the schema, such as explaining interactions between parameters or providing examples. Since the schema does the heavy lifting, the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Gets') and resource ('transaction history for a user and optional contract'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'get_transaction_info' or 'get_events', which might also retrieve transaction-related data, so it falls short of a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'get_transaction_info' or 'get_events', nor does it specify prerequisites or contexts for usage, leaving the agent to infer based on the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_transaction_infoB
Gets detailed information about a specific transaction
| Name | Required | Description | Default |
|---|---|---|---|
| network | Yes | The blockchain network (e.g., "ethereum", "polygon") | |
| txHash | Yes | The transaction hash to fetch details for |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. While 'Gets' implies a read-only operation, it doesn't specify authentication requirements, rate limits, error conditions, or what 'detailed information' includes. For a tool with no annotation coverage, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that communicates the core purpose without unnecessary words. It's appropriately sized for a simple lookup tool and front-loads the essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read operation with 2 well-documented parameters and no output schema, the description is minimally adequate. However, without annotations or output schema, it should ideally provide more context about what 'detailed information' includes and any behavioral constraints to compensate for the missing structured data.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with both parameters clearly documented in the schema itself. The description doesn't add any meaningful parameter semantics beyond what's already in the schema descriptions, so it meets the baseline expectation without adding extra value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Gets') and resource ('detailed information about a specific transaction'), making the purpose immediately understandable. However, it doesn't distinguish this tool from potential sibling tools like 'get_block_info' or 'get_transaction_history_for_user', which reduces its differentiation value.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With sibling tools like 'get_transaction_history_for_user' that might overlap in functionality, there's no indication of when this specific transaction lookup is appropriate versus broader history queries.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
read_contractC
Read contract state from a blockchain. important:
In case of a tuple, don't use type tuple, but specify the inner types (found in the source) in order. For nested structs, include the substructs types.
Example:
struct DataTypeA {
DataTypeB b;
//the liquidity index. Expressed in ray
uint128 liquidityIndex;
}
struct DataTypeB {
address token;
}
results in outputs for function with return type DataTypeA (tuple in abi): outputs: [{"type": "address"}, {"type": "uint128"}]| Name | Required | Description | Default |
|---|---|---|---|
| contract | Yes | The contract address | |
| inputs | Yes | Input parameters for the method call | |
| method | Yes | The contract method to call | |
| network | Yes | The blockchain network (e.g., "ethereum", "base") | |
| outputs | Yes | Expected output types for the method call. In case of a tuple, don't use type tuple, but specify the inner types (found in the source) in order. For nested structs, include the substructs types. Example: struct DataTypeA { DataTypeB b; //the liquidity index. Expressed in ray uint128 liquidityIndex; } struct DataTypeB { address token; } results in outputs for function with return type DataTypeA (tuple in abi): outputs: [{"type": "address"}, {"type": "uint128"}] |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It only mentions that this is a 'read' operation, but doesn't cover important aspects like whether it requires authentication, rate limits, network availability, error handling, or what the return format looks like. The example focuses on output formatting but doesn't explain the tool's operational behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is poorly structured - it starts with a purpose statement but immediately dives into complex formatting rules with a lengthy example. The formatting guidance should be in the parameter documentation, not the main description. The description is front-loaded with technical details rather than clear usage information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 5-parameter tool with no annotations and no output schema, the description is inadequate. It should explain what kind of data is returned, error conditions, network requirements, and how this differs from sibling tools. The current description focuses narrowly on output formatting while missing broader contextual information needed for effective tool selection and use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all 5 parameters thoroughly. The description adds no meaningful parameter semantics beyond what's in the schema - it only provides formatting rules for the 'outputs' parameter through an example, which is already covered in the schema's description field. This meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description starts with 'Read contract state from a blockchain' which clearly states the verb ('read') and resource ('contract state'), but it's vague about what 'contract state' entails compared to siblings like 'get_abi' or 'get_source'. It doesn't specify that this is for calling read-only contract methods, which would help distinguish it from other blockchain query tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'get_abi' or 'get_events'. The description focuses entirely on technical formatting requirements for outputs, with no mention of use cases, prerequisites, or comparisons to sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
10 tool updates
v1.0.0- First observed
build_event_topic - First observed
get_abi - First observed
get_block_info - First observed
get_events - First observed
get_proxy - First observed
get_source - First observed
get_token_balances_on_network - First observed
get_transaction_history_for_user - First observed
get_transaction_info - First observed
read_contract
TDQS
Every tool has a clearly distinct purpose with no ambiguity. For example, get_abi retrieves contract interfaces, get_events fetches logs, get_token_balances_on_network handles balances, and read_contract reads state—each targets a specific blockchain operation without overlap.
All tool names follow a consistent verb_noun pattern (e.g., get_abi, get_block_info, read_contract). The naming is uniform across all 10 tools, using snake_case and clear action-object pairs, making them predictable and easy to parse.
With 10 tools, this server is well-scoped for onchain data retrieval. Each tool earns its place by covering essential blockchain operations like reading contracts, fetching events, and getting transaction details, without being overly sparse or bloated.
The tool set provides strong coverage for reading and querying onchain data, including contracts, blocks, transactions, events, and balances. A minor gap exists in write operations (e.g., sending transactions or interacting with contracts), but agents can still handle most read-focused workflows effectively.
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