Simulate any read-only Ethereum contract call via eth_call — pass a contract address and encoded calldata, get the raw return value, across Base, Ethereum, Optimism, Arbitrum, Polygon, Gnosis. The universal contract-read primitive for agents that need a view function not covered by a dedicated endpoint. Live public RPC; one paid call.
| Name | Required | Description | Default |
|---|---|---|---|
| x_payment | No | Signed x402 payment payload |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the transparency burden. It discloses read-only behavior, 'Live public RPC', and 'one paid call,' which is useful context. However, it does not mention error behavior (e.g., reverts) or response formatting beyond 'raw return value,' leaving some 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?
Three sentences, each earning its place: the first defines the operation, the second clarifies use case, the third covers RPC and payment. Information is front-loaded, with no filler or redundancy.
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?
The description covers scope, chains, and payment, but the missing schema parameters and absence of an output schema leave critical gaps. The agent cannot determine how to input the actual call parameters, so the description is not yet complete for a tool of this complexity.
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 description mentions passing a contract address and encoded calldata, but the input schema only defines x_payment. The agent is not told how or where to supply these essential inputs, nor what encoding is expected for calldata. The schema mismatch makes the parameter semantics incomplete and confusing.
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 opens with a specific verb ('Simulate') and names the exact resource ('read-only Ethereum contract call via eth_call'), then lists supported chains. It distinguishes itself from siblings by framing it as the 'universal contract-read primitive' for view functions without a dedicated endpoint.
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?
Explicitly gives when-to-use guidance: use when a view function is 'not covered by a dedicated endpoint.' It also enumerates supported networks (Base, Ethereum, Optimism, etc.) and notes the paid nature, helping agents decide between this and more specialized tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Many tools occupy the same conceptual space: web_scrape vs markdown_web_scraper, post_check vs brand_ai_visibility_check, llm_chat_completions vs post_api_v1_chat_completions, chain_transaction_status vs chain_confirmations, and connect_token vs token_security_check + dex_token_data. Descriptions help in places, but for an agent facing 92 tools these near-overlapping endpoints will frequently cause misselection.
Everything is snake_case, but the conventions diverge sharply: get_chain_* and chain_* coexist for the same RPC family, post_* names are HTTP-route artifacts, api_generate reverses noun_verb order, and many names are bare nouns rather than verb_noun. There is no predictable naming pattern an agent can rely on.
At 92 tools this is far beyond the range where an agent can keep the surface coherent, even for a store. The flat tool list mixes products, bundles, aliases, proxies and single-use verticals, so most of the count is noise for any given task. A catalog/search/payment model with fewer exposed tools would fit the storefront purpose better.
The server has impressive breadth and covers key storefront/market workflows: catalog, samples, credits, directory listing, notary, and the task lifecycle. But each domain is shallow: there is no chain transaction broadcast, no task update/cancel/dispute, no AI-visibility history, and many verticals are a single tool with no follow-on operation. The surface is broad but not deeply complete.