WarpPay402 Gateway
I used the same url for two different postings.
Server Details
Production-grade MCP gateway delivering 8 real-time AI tools with instant x402 micropayments settled in USDC on Base Mainnet or SPL-USDC on Solana. Features Basescan contract auditing, wallet analytics, headless browser scraping, and pre-scraped oracle data feeds.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
Available Tools
15 toolsaerodrome_clammBInspect
Allows agents to open, adjust, and rebalance concentrated liquidity ranges on Aerodrome Slipstream ($0.01 USDC)
| Name | Required | Description | Default |
|---|---|---|---|
| action | Yes | ||
| token0 | No | ||
| token1 | No | ||
| tokenId | No | ||
| tickLower | No | ||
| tickUpper | No | ||
| amount0Desired | No | ||
| amount1Desired | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears the full burden of disclosing behavior. It mentions opening, adjusting, and rebalancing ranges but does not disclose that this likely executes on-chain mutations, potentially requires authentication or wallet signing, may incur gas/fees, or has side effects on existing positions.
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, concise sentence that front-loads the core purpose. It is slightly padded by 'Allows agents to', but remains efficient and easy to parse.
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 complex DeFi management tool with 8 parameters and no output schema or annotations, the description is too sparse. It omits action-specific prerequisites (e.g., needing an existing tokenId for adjust/collect), return behavior, and on-chain execution implications.
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 0%, and the description does not explain the parameters. It vaguely hints at ranges and actions, but does not clarify token0, token1, tickLower, tickUpper, amount0Desired, amount1Desired, or tokenId. The action enum is in the schema but not semantically elaborated in the description.
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 names specific actions ('open, adjust, and rebalance') and a specific resource ('concentrated liquidity ranges on Aerodrome Slipstream'). It clearly distinguishes this tool from siblings like aerodrome_swap and get_aerodrome_yields by focusing on liquidity range management rather than swapping or yield lookup.
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?
Usage context is implied: an agent would call this when managing concentrated liquidity positions on Aerodrome. However, there is no explicit guidance on when to use this tool versus alternatives such as aerodrome_swap or get_aerodrome_yields, and no exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
aerodrome_swapCInspect
Executes low-slippage token swaps directly via Aerodrome Finance Router on Base Mainnet ($0.01 USDC)
| Name | Required | Description | Default |
|---|---|---|---|
| tokenIn | Yes | ||
| amountIn | Yes | ||
| isStable | Yes | ||
| tokenOut | Yes | ||
| decimalsIn | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of disclosing behavior, but it only states that swaps are executed 'via Aerodrome Finance Router.' It does not disclose whether approvals are required, whether this is a mutating on-chain transaction, what happens on revert, or what the return value is. The ambiguous '$0.01 USDC' and 'low-slippage' phrasing provides limited additional transparency.
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 short and the main point is front-loaded, which is good. However, the parenthetical '($0.01 USDC)' is unexplained and adds ambiguity rather than clarity. The single sentence is compact but could be improved by replacing the vague parenthetical with useful operational context.
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?
This is a complex on-chain swap operation with five required parameters, no output schema, and no annotations, yet the description gives almost no operational context. It omits parameter meanings, swap output expectations, slippage handling, fee details, and any prerequisites such as token approval. An agent has insufficient information to invoke this tool correctly.
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 0% and the description provides no information about any of the five required parameters. An agent cannot infer the semantics of tokenIn, tokenOut, amountIn, decimalsIn, or isStable beyond their names. The description does nothing to compensate for the total lack of parameter documentation.
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 uses a specific verb ('Executes') and resource ('token swaps directly via Aerodrome Finance Router on Base Mainnet'), making the core function clear. It also distinguishes itself from sibling tools like get_aerodrome_yields, though it does not explicitly name alternatives. The parenthetical '($0.01 USDC)' is ambiguous but does not obscure the main purpose.
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 implies this tool should be used when token swaps on Aerodrome are needed, but it gives no explicit when-to-use or when-not-to-use guidance. It does not mention alternatives such as get_aerodrome_yields or any conditions that would make another tool preferable. Usage context is only implied, not stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
aerodrome_veaeroCInspect
Automates $AERO locking, epoch gauge voting, and bribe reward harvesting on Aerodrome ($0.01 USDC)
| Name | Required | Description | Default |
|---|---|---|---|
| action | Yes | ||
| amount | No | ||
| tokenId | No | ||
| lockDurationWeeks | No | ||
| poolVoteAddresses | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits, but it only summarizes high-level actions. It does not mention that these are likely on-chain mutating operations requiring signatures and gas, that lock changes may be irreversible, or that claiming bribes moves funds. The parenthetical '($0.01 USDC)' adds irrelevant noise.
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 short and reasonably front-loaded, but the price aside '($0.01 USDC)' is irrelevant and distracts from the operational content. The single-sentence format is acceptable but not tightly structured for swift parsing.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This is a multi-action, likely state-changing tool with five parameters, no output schema, and no annotations. The description does not cover per-action behavior, parameter constraints, prerequisites, or expected results, so an agent cannot reliably invoke it beyond knowing which actions exist.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate, but it does not explain amount units, tokenId semantics, lockDurationWeeks meaning, or poolVoteAddresses format. It only loosely connects the parameters to locking, voting, and bribes, leaving the agent to rely mostly on parameter names and the action enum.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the domain (Aerodrome), the asset ($AERO), and three concrete operation classes: locking, epoch gauge voting, and bribe harvesting. This distinguishes it from swap/liquidity/yield sibling tools, though the verb 'automates' is broad and the description does not explicitly name the sibling alternatives.
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?
There is no explicit guidance about when to use this tool versus aerodrome_swap, aerodrome_clamm, or get_aerodrome_yields. The intended use is only implied by the enumerated operations; no conditions, exclusions, or prerequisites are stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
base_analyticsAInspect
Fetches Base 0x wallet balance and nonce stats ($0.002 USDC)
| Name | Required | Description | Default |
|---|---|---|---|
| address | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses a per-call cost ($0.002 USDC), which is useful behavioral information beyond the schema. However, with no annotations, it does not mention output format, error behavior, authentication requirements, or rate limits, leaving several behavioral details undisclosed.
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?
A single well-structured sentence conveys the core function and cost with no filler. The essential information is front-loaded, which is ideal for a simple one-parameter tool.
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 fetch tool, the description is adequate but not fully complete. It lacks an explanation of the return payload and any usage context relative to siblings, and there is no output schema to compensate.
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 0%, but the description partially compensates by implying the 'address' parameter is a Base 0x wallet address. It does not clarify the required address format or chain details explicitly, so the semantic guidance remains thin.
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 uses a specific verb ('Fetches') and names a precise resource: Base 0x wallet balance and nonce stats. This clearly differentiates the tool from siblings like web_scraper or pdf_extractor, which serve unrelated purposes.
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 about when to use this tool versus alternatives such as data_feeds or public_data_feed. The cost hint is present, but there is no explicit context for selection or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
browser_scraperCInspect
Unblockable JS-rendering browser scraper ($0.005 USDC)
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations present, the description carries the full burden of disclosing behavior. It does reveal that the tool uses JS rendering and claims blocking resistance, plus a per-call price, but it omits response format, timeout behavior, rate limits, failure modes, and whether any side effects occur. This is thin coverage for an unannotated tool.
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 very short and front-loads the most useful differentiators before the price. It wastes no words, though it is so terse that it sacrifices usable guidance.
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 has no annotations, no output schema, and a single parameter with zero documentation, the description should compensate by explaining what is scraped, what the output looks like, and when it should be chosen over sibling tools. The current one-liner leaves these essential operational details implicit.
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 only parameter, 'url', has no schema description and the tool description adds nothing about it. An agent can guess that 'url' is the target page to scrape, but the description does not clarify accepted schemes, redirects, rendering waits, or expected input formats, leaving the parameter's semantics under-specified.
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 identifies the tool as a 'browser scraper' and adds the meaningful qualifiers 'unblockable' and 'JS-rendering', which distinguish it from a generic web scraper. It lacks an explicit verb and does not specify exactly what is returned, but the core purpose is clear.
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 qualifiers 'unblockable' and 'JS-rendering' imply the tool should be used for dynamic or anti-bot-protected pages, providing a soft usage cue. However, it does not explicitly state when to prefer this tool over siblings like web_scraper or render_screenshot, and gives no exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
data_feedsDInspect
Pre-scraped AI data feeds ($0.001 USDC)
| Name | Required | Description | Default |
|---|---|---|---|
| feedId | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the behavioral burden, but it only mentions that the feeds are pre-scraped and cost $0.001 USDC. It does not disclose what happens when feedId is provided, whether any side effects occur, or what the response looks like.
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 text is short, but it is an under-specified label rather than a concise tool description. It front-loads a useful cost detail but omits the necessary functional information, so brevity is not appropriate for the tool's needs.
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 tool with a required parameter, no output schema, and no annotations, the description is far too incomplete. An agent cannot determine what to pass, what will be returned, or how this tool differs from similar data-access siblings.
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 0%, so the description must explain the required feedId parameter. It does not: no source for feedId values, no format, no example, and no indication of how a caller would know a valid ID.
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 is a noun phrase ('Pre-scraped AI data feeds') with no action verb, so it mainly restates the tool name rather than explaining what the tool does (list, retrieve, or purchase feeds). It also does not distinguish this from the closely named sibling 'public_data_feed'.
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?
There is no explicit guidance about when to use data_feeds versus alternatives like web_scraper, browser_scraper, or public_data_feed. 'Pre-scraped' implies it is for already collected data, but this is left to inference rather than stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
deploy_contractCInspect
Deploys custom escrow, bounty, or agent smart contracts to Base Mainnet ($5.00 USDC)
| Name | Required | Description | Default |
|---|---|---|---|
| contractType | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of behavioral disclosure. It usefully reveals the cost ($5.00 USDC) and target network (Base Mainnet), but it does not mention that deployment is an on-chain write requiring funded wallet, that it may be irreversible, or what the response/confirmation behavior looks like. The contract-type mismatch between description and schema also undermines transparency about what operation is actually performed.
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 concise sentence that leads with the action verb and front-loads the most important facts: deployment, contract types, target network, and cost. Every word earns its place and there is 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?
Given a tool with no output schema, zero schema description coverage, and only one parameter, the description should fully document that parameter and the expected behavior. It fails to list the actual enum options and gives no information about what happens during or after deployment, required wallet balance, or return values. The mismatch between described types and schema enum leaves a significant completeness gap.
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 0%, so the description must explain the contractType parameter. It names 'escrow, bounty, or agent' but omits the valid enum values 'subscription' and 'pendle', and includes 'agent' which is not in the schema. This leaves an agent with incomplete and partially incorrect information about valid parameter values.
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 a verb and resource: deploying smart contracts to Base Mainnet, which distinguishes it from sibling tools like smart_contract_verifier. However, it lists contract types ('escrow, bounty, or agent') that conflict with the schema enum ('escrow, bounty, subscription, pendle'), introducing an invalid type ('agent') while omitting two valid ones, so the actual purpose scope is somewhat misleading.
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 given about when to use this tool versus alternatives such as smart_contract_verifier or base_analytics. The intended usage is merely implied by the verb 'deploys'; there are no exclusions, prerequisites, or conditions for selecting this tool over siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
deploy_solana_contractAInspect
Programmatically initializes SPL Escrows, cNFT Badge Issuers, or Raydium Vaults on Solana Mainnet ($5.00 USDC)
| Name | Required | Description | Default |
|---|---|---|---|
| params | No | ||
| contractType | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full disclosure burden and adds meaningful behavioral context: the operation is a state-changing on-chain action, it costs $5.00 USDC, and it targets Solana Mainnet (permanent, real-value, irreversible) rather than a testnet. It does not cover prerequisites like wallet/funds, failure modes, or idempotency, but the cost and network disclosures are highly material for an agent deciding whether to invoke.
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?
A single tightly-phrased sentence that front-loads the action verb, enumerates the three supported contract types, and appends the two most operationally relevant facts (network and fee). There is no filler, no repetition of the tool name, and every phrase 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?
The description is complete enough for tool selection: an agent can tell exactly when this is the right tool and roughly what it does. It falls short on invocation: 'params' is opaque, there is no output schema or description of what a successful deploy returns, and no mention of wallet or funding prerequisites. For a paid mainnet deployment with three distinct contract types, input and result behavior should be better specified.
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 0%, so the description must compensate, and it partially does: it translates the cryptic enum keys (spl_escrow, cnft_badge, raydium_vault) into human-readable contract type names. However, the 'params' nested object is never mentioned, leaving its content and per-type structure entirely to inference. The compensation is real but incomplete.
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 uses a specific verb ('initializes') with concrete resources ('SPL Escrows, cNFT Badge Issuers, Raydium Vaults') on an explicit network ('Solana Mainnet'). It names exactly three deployable contract types that map directly to the schema enum, and adds the operational detail of a $5.00 USDC fee. This unmistakably identifies it as the blockchain deployment tool among unrelated siblings like base_analytics and browser_scraper.
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 gives clear context for when to use this tool: whenever an SPL Escrow, cNFT Badge Issuer, or Raydium Vault needs to be created on Solana Mainnet. It does not explicitly state when-not-to-use scenarios or name alternatives, but the sibling set (analytics, scraping, data feeds) is so different in domain that an agent would not confuse them. The fee disclosure also implicitly signals a budget prerequisite.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
extract_jsonBInspect
Extracts structured JSON data from web pages ($0.01 USDC)
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes |
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 mentions a cost, but does not disclose error behavior, success criteria, limits, authentication needs, or whether the extraction works on dynamic/JavaScript-rendered pages.
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 front-loaded sentence that communicates the core purpose and cost with zero wasted words. It 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 the tool's simplicity (one parameter, no output schema, no annotations), the description provides the minimal essentials: input URL, output type, and cost. However, it lacks guidance on choosing between this and sibling scrapers, and it omits behavioral caveats that an agent would benefit from knowing.
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 0%, so the description must compensate. The phrase 'from web pages' clarifies that the single required 'url' parameter should point to a web page. This adds meaning beyond the schema's bare type string, but the description could still be more explicit about accepted URL formats or constraints.
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 uses a specific verb ('Extracts') and identifies both the resource ('web pages') and the output format ('structured JSON data'). It is clear about what the tool does, though it does not explicitly distinguish itself from sibling web-scraping tools like web_scraper or browser_scraper.
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 implies when to use the tool: when structured JSON needs to be extracted from a web page. However, it gives no explicit guidance about when not to use it or which sibling tools might be better alternatives for other scraping or parsing needs.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_aerodrome_yieldsAInspect
Fetch live Aerodrome DEX pool yields, APYs, and TVL on Base Mainnet ($0.003 USDC)
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the behavioral burden. It does disclose 'live' data and a per-call cost of $0.003 USDC, which is useful. However, it does not mention authentication needs, rate limits, caching behavior, or what happens if the DEX feed is unavailable.
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, front-loaded sentence with no filler. It packs the resource, chain, data types, and a cost disclosure into a compact and readable format.
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 parameterless fetch tool, this description is mostly complete: it states what data is returned, where it comes from, and the cost. It could be slightly stronger with an indication of the return shape, but the simple interface and explicit resource make it sufficient for selection and invocation.
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 tool has zero parameters and 100% schema description coverage, so there is no parameter semantics burden for the description. The baseline of 4 applies because there is nothing the description needs to clarify.
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 a specific verb ('Fetch'), resource ('Aerodrome DEX pool yields, APYs, and TVL'), and scope ('Base Mainnet'). It is immediately distinguishable from generic siblings like data_feeds or public_data_feed by naming the exact protocol and data types.
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 gives no guidance on when to use this tool versus alternatives such as data_feeds, public_data_feed, or base_analytics. It does not mention exclusions or conditions that would route an agent to a different sibling.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
pdf_extractorAInspect
Extracts plain text preview from public PDF URLs ($0.005 USDC)
| Name | Required | Description | Default |
|---|---|---|---|
| pdfUrl | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full behavioral burden. It does add useful context: only public PDFs are supported, the output is a plain text preview, and there is a $0.005 USDC cost. It does not disclose failure behavior, size limits, or truncation details, which would be valuable.
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?
A single, well-structured sentence communicates the action, target, output type, and cost with zero filler. Every word contributes meaning.
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 one-parameter tool, the description is minimally viable: it names the input and output type. However, without annotations or an output schema, it should also clarify what 'preview' means, how much text is returned, and what happens for invalid or inaccessible PDFs.
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 coverage is 0% and the pdfUrl parameter has no description, so the description must compensate. It clarifies that the parameter should be a public PDF URL, but it does not specify additional format details, download-link requirements, or accessibility constraints.
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?
Description uses the specific verb 'Extracts' with a clear resource: 'plain text preview from public PDF URLs'. This distinguishes it from sibling tools like web_scraper, extract_json, and render_screenshot, making the tool's purpose immediately obvious.
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 implies when to use the tool: when the target is a public PDF URL and plain text is needed. However, it does not explicitly state when not to use it or mention alternatives for non-PDF or private documents, leaving some routing judgment to the agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
public_data_feedDInspect
Public attestation data feed JSON records ($0.0001 USDC)
| Name | Required | Description | Default |
|---|---|---|---|
| filename | Yes |
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 does mention that the data is public and that records cost $0.0001 USDC, which are useful signals, but it does not describe access requirements, side effects, pagination, rate limits, or response characteristics.
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 very short, but this is under-specification rather than effective conciseness. It is a fragment without a clear statement of action or parameter semantics, so brevity does not compensate for the missing essential content.
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?
With no output schema, no annotations, an undocumented parameter, and several potentially related sibling tools, the description is not nearly complete enough for an agent to confidently select or invoke the tool. It fails to explain input, output, cost trigger, or how it differs from data_feeds.
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 has one required parameter, 'filename', with no description, and schema description coverage is 0%. The tool description does not mention 'filename' at all, so an agent cannot know whether it is a URL, a key, a path, or some other identifier.
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 is a noun phrase: 'Public attestation data feed JSON records ($0.0001 USDC)'. It identifies a resource and output format, but lacks any verb such as fetch, list, or retrieve, so an agent cannot be certain what action the tool performs. It also does not differentiate this from the sibling 'data_feeds' tool.
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?
There is no guidance on when to use this tool versus alternatives like data_feeds, extract_json, or web_scraper. The description merely states cost and data type, leaving the selection criteria entirely to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
render_screenshotBInspect
Captures rendered webpage screenshot image data ($0.01 USDC)
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It mentions the page is 'rendered' and notes the cost, but does not describe output format, execution behavior, potential failures, or any side effects. This is thin behavioral context for an operation that produces image data.
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, focused sentence with no filler. The verb and resource are front-loaded, and the cost detail is included without distracting from the core purpose.
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 single-parameter tool, the description is mostly adequate, but it leaves ambiguity about the output format (e.g., PNG, JPEG, base64) and whether any URL restrictions apply. The missing output schema means these details should have been in the description; an agent cannot reliably know how to consume the 'screenshot image data' result.
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?
With 0% schema description coverage, the description must compensate for the undocumented 'url' parameter. It adds the context that the URL refers to a 'webpage', but it does not specify expected URL format, accessibility requirements, or what constitutes a valid input. The parameter name is self-explanatory enough to reach a baseline, but no additional semantics are 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 uses a specific verb ('Captures') and a concrete resource ('rendered webpage screenshot image data'), making the tool's basic function immediately clear. It inherently differentiates itself from content-scraping siblings, though it does not explicitly name or contrast them.
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 web_scraper or browser_scraper. There is no mention of suitability conditions, exclusions, or selection criteria, leaving the agent to infer usage purely from the tool's name and function.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
smart_contract_verifierCInspect
Source code analysis, ABI fetching, and proxy validation ($0.02 USDC)
| Name | Required | Description | Default |
|---|---|---|---|
| address | Yes |
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 does disclose the $0.02 USDC cost, which is useful, but it does not mention whether the operation is read-only, what happens on failure, whether network/chain context is required, or any rate limits. The behavioral picture is incomplete.
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 compact sentence that front-loads the main capabilities and appends the cost. There is no filler or redundancy. It loses one point because the noun-phrase list is terse and would benefit from a clearer verb or structured phrasing.
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?
With no output schema and no annotations, the description should explain what the tool returns, any prerequisites, and the expected address context. It does none of these. The cost and capability list give a starting point, but an agent would still lack critical information needed to confidently invoke and interpret the tool.
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 only defines a string 'address' with 0% description coverage, so the description must compensate. It does imply the address is a smart-contract address relevant to source/ABI/proxy verification, but it does not specify expected format, chain, checksumming, or whether the address must be verified first. This is partial but insufficient compensation.
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 names three concrete capabilities — source code analysis, ABI fetching, and proxy validation — and the tool name identifies the smart-contract domain. It clearly differentiates from the listed siblings, which are generic scraping/analytics tools. It loses a point for lacking an explicit verb and not defining what 'proxy validation' entails.
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 given on when to use this tool versus alternatives, what preceding or subsequent steps are expected, or what conditions make it appropriate. The description simply lists capabilities and price, leaving the agent to infer usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
web_scraperCInspect
Scrapes web pages into clean markdown ($0.001 USDC)
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the full burden of behavioral disclosure. It reveals the output format and price, but does not mention whether JavaScript is executed, what URL schemes are accepted, failure behavior, rate limits, or access restrictions. This is insufficient for a scraping tool with an ambiguous sibling.
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 sentence with no filler; the core action, output format, and cost are front-loaded. It is appropriately terse for a tool with only one parameter, though the brevity sacrifices needed guidance.
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 tool with no output schema and no annotations, the description is too sparse to be self-sufficient. It omits the exact return shape, URL requirements, and when to prefer this over browser_scraper, so an agent lacks enough context to invoke it reliably in ambiguous situations.
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 one 'url' parameter with 0% description coverage, and the tool description does not explain accepted URL formats or constraints. The property name and 'web pages' phrasing imply an HTTP URL, but no additional semantics are provided beyond the schema.
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 states a specific action ('scrapes') and a concrete output ('clean markdown'), so an agent understands roughly what the tool produces. However, it does not distinguish itself from the sibling 'browser_scraper', which likely has overlapping functionality, so full differentiation is missing.
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 given for when to choose this tool over browser_scraper, render_screenshot, or pdf_extractor. The description provides no explicit conditions, exclusions, or alternative recommendations, leaving the agent to guess 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.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
2 tool updates
- Added
aerodrome_clamm - Added
aerodrome_veaero
1 tool update
- Added
aerodrome_swap
1 tool update
- Changed
deploy_solana_contract2 fields changed- removed
Input schema / properties / contractType / descriptionRemoved value: -"Solana program state architecture to initialize" - removed
Input schema / properties / params / descriptionRemoved value: -"Parameters for initialization (e.g., mints, fee rates, merkle trees)"
1 tool update
- Added
deploy_solana_contract
1 tool update
- Changed
deploy_contract1 field changed- changed
Input schema / properties / contractType / enumPrevious value: -[ - "escrow", - "bounty", - "subscription" -]New value: +[ + "escrow", + "bounty", + "subscription", + "pendle" +]
1 tool update
- Added
deploy_contract
1 tool update
- Added
get_aerodrome_yields
9 tool updates
- First observed
base_analytics - First observed
browser_scraper - First observed
data_feeds - First observed
extract_json - First observed
pdf_extractor - First observed
public_data_feed - First observed
render_screenshot - First observed
smart_contract_verifier - First observed
web_scraper
Frequently Asked Questions
Claiming proves that you control a remote MCP connector. It does not move, proxy, or interrupt the server.
Open the connector listing, choose Claim ownership, and sign in to Glama.
Complete one verification method:
GitHub identity — fastest for official registry listings. For a namespace such as
io.github.alice/server, link the matching GitHub user, then choose Claim with GitHub. An organization namespace such asio.github.acme/serveralso needs that organization to have installed the Glama AI GitHub App and approved its permissions, because GitHub discloses organization membership only to apps it has installed. Use HTTP or DNS when it has not.HTTP challenge — works when you can deploy a public file. Generate a token, publish the exact JSON Glama shows at
/.well-known/glama.jsonon the same origin as the connector, then choose Check HTTP challenge.DNS challenge — works when you control DNS but cannot change the server. Generate a token, create the exact TXT record Glama shows, wait for it to propagate, then choose Check DNS challenge.
After verification, Glama sends a confirmation email and gives you access to listing details, thumbnails, health checks, and analytics. Keep the HTTP file or DNS record in place: Glama periodically checks it and ownership remains verified while the token is discoverable.
The HTTP ownership file has this structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"claim": "glama_claim_..."
}Claim tokens are opaque, stable, and bound to the signed-in Glama account. They contain no email address or other personal information. If Glama can no longer discover a verified HTTP or DNS token, it starts a seven-day grace period before removing claim-based access. Restore the same token during that period to keep ownership verified. Never publish an email address, Glama session token, GitHub token, or connector credential as ownership proof.
If verification fails, confirm that you copied the current token exactly. The HTTP file must be public, return valid JSON with a successful HTTP response, and stay on the connector's origin. DNS changes may need more time to propagate. A claim cannot transfer to a different origin or hostname: if the connector target changes, Glama starts the grace period and the new target must be claimed separately after the previous claim is released.
For a connector linked to the official MCP Registry, registry updates continue to replace its name, description, and URL by default. After claiming, open Manage connector and enable Use Glama listing details as the source of truth if edits made on Glama should be preserved. Categories and thumbnails are always managed on Glama; registry linkage and technical connection settings continue to sync.
Control your server's listing on Glama, including description and metadata
Access analytics and receive server usage reports
Get monitoring and health status updates for your server
Feature your server to boost visibility and reach more users
To improve your MCP server's ranking:
Claim ownership of the server listing
Complete the server profile with an accurate description and thumbnail
Provide a test profile so Glama can connect to and evaluate the server
Keep tool definitions clear and complete to earn a high Tool Definition Quality Score (TDQS)
Route real usage through the Glama Gateway; more recorded successful server uses also improve the ranking
For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
Centralized credential management – store and rotate API keys and OAuth tokens in one place
Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
The server is experiencing an outage
The URL of the server is wrong
Credentials required to access the server are missing or invalid
If you are the owner of this MCP connector and would like to make modifications to the listing, including providing test credentials for accessing the server, please contact support@glama.ai.
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Glama MCP Gateway
Add one secure layer between your agents and this server.
TDQS
Several tools cluster around web content retrieval: web_scraper, browser_scraper, extract_json, and render_screenshot all pull from web pages and could be confused. data_feeds and public_data_feed also sound similar. Most other tools have distinct purposes, but these overlapping clusters create real selection ambiguity.
Tool names mix verb-led conventions like deploy_contract, extract_json, and render_screenshot with noun-led names like browser_scraper, pdf_extractor, and smart_contract_verifier. Pairs such as web_scraper vs browser_scraper and extract_json vs pdf_extractor are also stylistically inconsistent.
Twelve tools is a reasonable count for a paid gateway offering data extraction, feeds, and contract deployment. However, the scraping/extraction cluster is somewhat redundant, so the set could be tightened without losing much functionality.
The toolset broadly covers web data extraction, PDF processing, feeds, Base/Solana contract deployment, and blockchain analytics. Notable gaps include the lack of Solana-side balance/analytics tools and any post-deployment contract interaction or management capability.