Automaton Colony
Server Details
Smart-contract and B20 token screening on Base. Free on-chain check (verified source, proxy, admin selectors, holder concentration), paid Flash Audit over x402 (3.49 USDC) returning a report with an anchored SHA-256. No API key: payment is the only gate, handled inside the tool via x402/payment metadata.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
Available Tools
4 toolsbuy_flash_auditBuy a Flash Report (paid, x402)AInspect
Paid over x402 in USDC on Base. Without a payment in _meta["x402/payment"] it returns the PaymentRequired document (isError). With a valid PaymentPayload it validates, settles asynchronously and returns an orderKey to collect with collect_flash_audit.
| Name | Required | Description | Default |
|---|---|---|---|
| language | No | Report language. Defaults to "en". | |
| targetAddress | Yes | Contract or B20 token address on Base mainnet (eip155:8453), 0x + 40 hex. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses behaviors beyond the annotations: without a payment it returns a PaymentRequired error, with a valid payload it validates and settles asynchronously, and it returns an orderKey. The annotations only say readOnly=false and idempotent=false, so the description carries and richly satisfies the behavioral disclosure burden.
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?
Two dense sentences deliver the payment prerequisite, the error path, the asynchronous settlement, and the follow-up collect step with no wasted words. Technical terms like x402 and PaymentPayload are packed in without padding.
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 paid asynchronous flow with no output schema, the description covers what an agent needs: how the transaction is paid, what happens on missing payment, what a successful call returns, and which sibling to call next. The remaining x402 mechanics are outside the tool schema and do not block 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?
Schema coverage is 100%: targetAddress has format and chain details and language has an enum plus default. The description adds no parameter-specific meaning, which is acceptable because the schema already fully documents the parameters; baseline 3 applies.
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 frames the tool as a paid x402 purchase of a flash audit: it sends USDC on Base, validates a PaymentPayload, settles asynchronously, and returns an orderKey. It also distinguishes itself from the collect sibling by explicitly naming collect_flash_audit as the follow-up step.
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?
It gives clear context: use it when you have a payment x402 and want to buy a flash audit, and then use collect_flash_audit with the returned orderKey. It does not explicitly spell out when to prefer check_contract_free or flash_audit_terms, so the guidance is strong but not exhaustive.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
check_contract_freeFree check of a Base contractARead-onlyIdempotentInspect
Free, no wallet. Observed on-chain facts about a Base address with no verdict and no score: verified source, proxy detection, admin selectors, holder concentration, and for B20 native tokens the issuer powers. Rate limited; a monthly quota applies.
| Name | Required | Description | Default |
|---|---|---|---|
| address | Yes | Contract or B20 token address on Base mainnet (eip155:8453), 0x + 40 hex. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, so the safety profile is covered there. The description adds meaningful behavioral context: no wallet needed, no verdict or score, observed on-chain facts only, rate limiting with a monthly quota. This goes beyond the annotations and sets correct expectations about 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?
Two sentences with no filler. The most decision-relevant facts are front-loaded: 'Free, no wallet' and 'no verdict and no score'. The description then efficiently lists what the check covers and closes with practical rate-limit information. Every clause 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?
For a single-parameter, no-output-schema tool, the description is complete enough for an agent to decide whether and how to call it. It explains the free/no-wallet nature, the output scope (facts, not verdicts), the main returned fact types, and the rate-limit constraint. No critical information appears missing.
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 already covers the single parameter fully with a regex, a description of the expected address, and a network qualifier. The tool description reinforces that this is a Base address and mentions B20 native tokens, but it does not add significant semantic detail beyond the schema. With 100% schema description coverage, the baseline 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 states a specific verb and resource: it performs a free check of a Base address/contract. It clearly scopes the tool to observed on-chain facts with no verdict and no score, and enumerates the fact categories (verified source, proxy detection, admin selectors, holder concentration, issuer powers). This strongly differentiates it from the flash-audit siblings, which imply paid, scored audit outcomes.
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 this tool is appropriate: free, no wallet required, and useful for quick on-chain facts without a verdict/score. It also warns about rate limiting and monthly quota. It does not explicitly name alternatives or state when-not-to-use, but the context is strong enough to guide selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
collect_flash_auditCollect a Flash Report orderARead-onlyIdempotentInspect
Status of an x402 order while it settles and generates; once DELIVERED, the report JSON itself. Poll every 10-15 seconds. Free.
| Name | Required | Description | Default |
|---|---|---|---|
| orderKey | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Despite already having readOnlyHint, idempotentHint, and destructiveHint annotations, the description adds genuinely useful behavior: polling cadence, the DELIVERED state transition, and that the operation is free. This goes beyond what annotations alone communicate and does not contradict them.
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?
Two short sentences deliver the core behavior, the polling interval, and the cost model with no filler. The key information is front-loaded and every clause 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?
For a single-parameter polling tool with no output schema, the description tells an agent what to expect (status while settling, JSON when DELIVERED), how often to poll, and that it costs nothing. It does not enumerate possible intermediate statuses or a max polling horizon, but those are minor gaps given the simple shape.
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 provides only the orderKey parameter with a hex pattern and no description, so the description carries responsibility for explaining its meaning. It ties the parameter to 'an x402 order,' providing some resource context, but it does not explain where the key comes from or how it relates to the order lifecycle. This is adequate but 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 names a specific behavior (poll/collect status) and a specific resource (x402 order), then clarifies the eventual output (report JSON once DELIVERED). This clearly distinguishes collect_flash_audit from sibling buy_flash_audit, which would be the order-creation counterpart.
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?
It gives strong usage context: this is a polling operation to be repeated every 10-15 seconds while the order settles and generates. It does not explicitly name alternatives or state when not to use it, but the lifecycle framing makes the intended use clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
flash_audit_termsFlash Report payment terms (x402)ARead-onlyIdempotentInspect
Returns the x402 v2 PaymentRequired document for the paid Flash Report: amount in USDC base units, network, asset, payTo and the request schema. Free.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds useful behavioral context beyond that: it returns a PaymentRequired document and is 'Free.' No contradiction with annotations exists.
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?
One tight sentence front-loads the main purpose, lists the returned fields, and closes with 'Free.' Every word carries information; 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?
With no output schema, the description carries the burden of explaining return values, and it does so by naming the document type and its key fields. Terms like 'USDC base units' and 'request schema' could be slightly more explicit, but for a zero-parameter, read-only retrieval tool this is largely sufficient.
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 schema description coverage is 100%, so the baseline is 4. The description correctly avoids inventing parameter details, and there is nothing for it to compensate for in the input 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 verb ('Returns') and a specific resource ('x402 v2 PaymentRequired document for the paid Flash Report'), and lists the exact contents (amount, network, asset, payTo, request schema). This clearly distinguishes it from sibling tools like buy_flash_audit and collect_flash_audit, which are about purchasing and collecting rather than retrieving terms.
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 its role as a read-only way to obtain payment terms and notes 'Free,' but it never explicitly says when to use this tool versus siblings like buy_flash_audit, collect_flash_audit, or check_contract_free. No alternatives or exclusions are named, so an agent must infer its usage context from the resource name and sibling list.
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.
4 tool updates
- First observed
buy_flash_audit - First observed
check_contract_free - First observed
collect_flash_audit - First observed
flash_audit_terms
Frequently Asked Questions
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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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TDQS
The buy, collect, and terms tools are clearly separated into payment, retrieval, and quote steps, and check_contract_free is a distinct free fact-check. The only mild ambiguity is that buy_flash_audit without payment also returns the same PaymentRequired document that flash_audit_terms exists to provide.
Most tools follow a verb_noun snake_case pattern, such as buy_flash_audit, collect_flash_audit, and check_contract_free. However, flash_audit_terms is a noun phrase, and check_contract_free embeds an adjective awkwardly, so the pattern is not fully uniform.
Four tools cover the narrow paid-and-free audit flow without bloat. Each tool maps to a necessary step: free facts, terms, purchase, and collection.
The paid audit lifecycle is complete: fetch terms, buy to get an orderKey, collect until delivered, plus a free no-wallet check for users who do not need a paid report. There are no obvious dead ends for the server's stated contract-inspection purpose.