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licenseB
qualityC
maintenanceEnables AI agents to perform token security audits, honeypot detection, liquidity analysis, and risk scoring to avoid crypto scams.
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vetagent
by dev.vetagent
Server Details
Pre-trade safety check for AI agents: honeypot, tax, liquidity and rug risk before you buy.
If you are the author of this connector, you can claim ownership with GitHub, an HTTP challenge, or a DNS record. Claimed connector authors can inspect health checks, view analytics, and manage their listing.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- jakegu1/vetagent
- GitHub Stars
- 0
Available Tools
3 toolsassess_token_riskAssess Token RiskARead-onlyIdempotentInspect
Safety check to run BEFORE buying, holding, or recommending a token. Returns an actionable verdict (low / medium / high / unknown), a 0-100 risk score, and the individual signals behind it. Covers: sell simulation (honeypot detection, buy/sell/transfer taxes), liquidity depth, trading-pair age, cross-chain presence, whether the contract is open source, and on Solana the mint/freeze authority and holder concentration — plus the aggregate verdicts of upstream security scanners. IMPORTANT: risk_level 'unknown' means a critical check could not be completed. It is NOT a low-risk result and must not be used to justify a trade; evidence.data_gaps lists exactly what was missing. 'confidence' measures how complete the input data was, not how safe the token is. Reports observable on-chain risk only. Not financial advice, does not size positions, and cannot see off-chain risk such as team behaviour, social engineering, or a rug executed through governance. Treat 'low' as 'no fatal signal found in the checks that ran', never as 'safe to buy'.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| address | Yes | Token contract address: ERC-20 (0x + 40 hex) or Solana (base58) | |
| verbose | No | Return full upstream evidence. Off by default to save tokens. | |
| chain_hint | No | Optional chain name (ethereum / bsc / base / polygon / arbitrum / solana). Strongly recommended: Ethereum forks such as PulseChain inherit contract addresses, so the same address exists on several chains at wildly different prices. |
Output Schema
ParametersJSON Schema
| Name | Required | Description |
|---|---|---|
| address | Yes | |
| signals | Yes | |
| evidence | No | |
| confidence | Yes | How complete the input data was — not how safe the token is. |
| risk_level | Yes | 'unknown' means a critical check could not be completed. It is NOT a low-risk result and must not justify a trade. |
| risk_score | Yes | 0-100; higher is more dangerous |
| recommendation | No |
TDQS
A4.5/5.0
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the readOnlyHint, openWorldHint, idempotentHint, and destructiveHint annotations, the description discloses critical behavioral semantics: risk_level 'unknown' means a check could not be completed and must not justify a trade, 'confidence' measures input completeness rather than safety, and 'low' is framed as 'no fatal signal found', not 'safe to buy'. This is exactly the kind of context an agent needs to interpret the result correctly.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose and return value, then systematically covers the signal categories, the critical 'unknown' caveat, and the tool's limitations. Although it is longer than a typical one-liner, every sentence carries meaningful guidance for a safety-critical tool and none feels redundant.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity, rich annotations, and the presence of an output schema, the description covers everything an agent needs for correct selection and invocation: use case, output semantics, non-obvious failure modes, limitations, and an explicit warning about the chain_hint parameter in the schema. No material gap remains.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the input schema already documents all three parameters, including the 'chain_hint' guidance about Ethereum forks. The tool description does not add per-parameter details, and with full schema 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.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb and resource: 'Safety check to run BEFORE buying, holding, or recommending a token. Returns an actionable verdict (low / medium / high / unknown), a 0-100 risk score, and the individual signals behind it.' This clearly distinguishes it from sibling tools like find_new_hot_pools (pool discovery) and get_token_liquidity (liquidity-only) by enumerating its broader risk-assessment scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use the tool ('BEFORE buying, holding, or recommending a token') and provides important exclusions ('Not financial advice, does not size positions, cannot see off-chain risk'). However, it does not explicitly name sibling tools or contrast them with this one, so the score stops short of a full 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
find_new_hot_poolsFind New Hot PoolsARead-onlyInspect
Scan a chain for the newest and most active trading pools, returning name, price, liquidity, 24h volume and pool age. Discovery only. New pools carry inherently high risk and appearing here is NOT a safety endorsement — call assess_token_risk on anything you intend to act on.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| chain | No | Chain name, e.g. solana / ethereum / base / bsc | solana |
| limit | No |
TDQS
A4.4/5.0
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already mark the tool as read-only, open-world, and non-destructive, so the description does not need to restate those. It adds meaningful behavioral context by emphasizing that results are discovery-only, carry high inherent risk, and are not a safety endorsement, which shapes how the agent should interpret and follow up on results.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no filler: the first states the action and output fields, the second delivers the critical risk warning and routing instruction. The most important behavioral caveat is front-loaded and every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple discovery tool with two optional parameters, annotations, and no output schema, the description covers the return fields, risk profile, and follow-up action. It does not restate the annotation-provided safety hints, and the only small gap is that limit semantics are left entirely to the schema constraints, which are clear enough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 50%: chain has a description, but limit has none. The description reinforces the chain concept by saying 'Scan a chain' but does not explain the limit parameter, its default, or its effect on the result set. The schema's min/max/default values partially compensate, so the description adds only marginal value beyond the structured fields.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific action ('Scan a chain'), a specific resource ('trading pools'), and the exact return fields (name, price, liquidity, 24h volume, pool age). This clearly distinguishes it from sibling tools: assess_token_risk evaluates risk, get_token_liquidity retrieves liquidity, while this tool discovers new active pools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly frames the tool as 'Discovery only' and states that appearing here is not a safety endorsement, directly instructing the agent to 'call assess_token_risk on anything you intend to act on.' This tells the agent when to stop after discovery and which sibling to use next, though it does not mention get_token_liquidity as an alternative, which is less critical here.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_token_liquidityGet Token LiquidityARead-onlyIdempotentInspect
Liquidity snapshot for a token's primary trading pair: price, 24h volume, pair count and the chains it trades on. Check 'status' before using the numbers. 'ok' means real data. 'unavailable' means the upstream request failed, which does NOT mean the token has no liquidity. 'not_found' means no trading pair exists for this address at all. 'unpriced' means pairs exist but no source has costed them, so liquidity_usd is null and the depth is unknown -- this is NOT a report of zero liquidity. 'drained' means every pool on the token's own chain reports its depth and every one is empty: there is nothing to sell into.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| address | Yes | Token contract address | |
| chain_hint | No | Optional chain name; disambiguates forks that share addresses |
Output Schema
ParametersJSON Schema
| Name | Required | Description |
|---|---|---|
| chains | No | |
| status | Yes | |
| address | Yes | |
| price_usd | No | |
| pairs_total | No | |
| served_stale | No | Present only when an upstream was unreachable and this answer used cached data. Each entry names the source and how many seconds old it was. |
| liquidity_usd | No | |
| volume_24h_usd | No |
TDQS
A4.1/5.0
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already declare readOnlyHint, openWorldHint, idempotentHint, and non-destructive behavior. The description adds essential behavioral nuance beyond the annotations, especially the critical warnings that 'unavailable' does not mean zero liquidity and 'unpriced' is not a report of zero liquidity. This prevents an agent from drawing false conclusions from the data.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The main capability is front-loaded in one precise sentence, followed by compact status definitions that each explain a distinct outcome. Every sentence earns its place and there is no filler or redundant restatement.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that an output schema exists and annotations cover the safety profile, the description adds exactly the missing operational knowledge: the meaning and correct interpretation of every status value. For a two-parameter read-only tool, nothing needed to invoke it correctly and use its results safely is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already documents both parameters with 100% coverage, so the baseline applies. The description does not add parameter-level detail, but none is needed because the schema sufficiently explains 'address' and 'chain_hint'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the resource ('a token's primary trading pair') and the specific data returned (price, 24h volume, pair count, chains), making the operation unambiguous. It is distinct from the risk assessment and hot-pool discovery siblings, but it does not explicitly name or differentiate itself from them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is implied through the phrase 'Liquidity snapshot' and by the tool's name, but there is no explicit statement of when to use this tool versus alternatives. The description does give valuable post-call guidance about interpreting the status field, but that is not tool-selection guidance.
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.
1 tool update
- Changed
get_token_liquidity3 fields changed- changed
Output schema / properties / liquidity_usd / typePrevious value: -"number"New value: +[ + "number", + "null" +] - added
Output schema / properties / served_staleAdded value: +{ + "description": "Present only when an upstream was unreachable and this answer used cached data. Each entry names the source and how many seconds old it was.", + "items": { + "type": "object" + }, + "type": "array" +} - changed
Output schema / properties / status / enumPrevious value: -[ - "ok", - "not_found", - "unavailable" -]New value: +[ + "ok", + "not_found", + "unpriced", + "drained", + "unavailable" +]
3 tool updates
- First observed
assess_token_risk - First observed
find_new_hot_pools - First observed
get_token_liquidity
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TDQS
A4.3/5.0
Disambiguation5/5
Each tool targets a distinct job: assess_token_risk returns a safety verdict, find_new_hot_pools discovers pools, and get_token_liquidity returns raw liquidity data. The slight thematic overlap around liquidity is handled clearly by the descriptions.
Naming Consistency5/5
All three tool names follow the same verb_noun snake_case pattern: assess_token_risk, find_new_hot_pools, get_token_liquidity. The verbs clearly map to the action each tool performs.
Tool Count5/5
Three tools is a tight, well-scoped set for a token-vetting server: discover pools, assess risk, and inspect liquidity. Each tool earns its place and none feels redundant.
Completeness3/5
The core lifecycle is covered, but find_new_hot_pools returns only name, price, liquidity, volume, and pool age, without an explicit token or pool address, making the intended handoff to assess_token_risk awkward. The risk assessment itself is comprehensive, but the discovery-to-vetting flow has a notable gap.