x402 Finance
Server Details
Live crypto market data on Base via x402 V2. $0.002 USDC per call. No API key. MCP + REST.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
Available Tools
3 toolsanalyze_holder_clustersAInspect
Analyze holder concentration and coordinated wallet clusters for a Base token. Cost: $0.01 USDC via x402. COMING SOON – not accepting payments yet.
| Name | Required | Description | Default |
|---|---|---|---|
| address | Yes | Token contract address on Base (0x...) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the full burden. It discloses the cost ($0.01 USDC via x402) and availability (COMING SOON – not accepting payments yet), which are valuable behavioral traits. It does not explicitly state read-only nature or describe the return format, but the core constraints are present.
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 two sentences plus a brief cost statement, all front-loaded and purposeful. No unnecessary words; every element contributes to understanding the 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 tool with one parameter, no output schema, and no annotations, the description provides the essential context: purpose, cost, and unavailability. The 'coming soon' status is critical for an agent to avoid invoking it. The lack of output details is acceptable given the tool is not yet active.
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% for the single parameter 'address', which already includes a description. The tool description adds no further semantics about the parameter beyond mentioning 'Base token', already captured in 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 uses the specific verb 'Analyze' and clearly identifies the resource: 'holder concentration and coordinated wallet clusters for a Base token'. This distinguishes it from sibling tools like check_token_safety and get_market_data, which focus on safety and market data respectively.
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 usage: if you need to analyze holder concentration, use this tool. However, it does not explicitly state when to use it over alternatives, nor does it provide exclusions or prerequisites beyond the Base token context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
check_token_safetyAInspect
Analyze a Base token for honeypot risk, taxes, liquidity and ownership. Returns risk_score, recommendation, agent_action (block|warn|allow|skip), and data_quality. Cost: $0.04 USDC via x402. LIVE.
| Name | Required | Description | Default |
|---|---|---|---|
| address | Yes | Token contract address on Base (0x...) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the return fields (risk_score, recommendation, agent_action, data_quality), the cost ($0.04 USDC via x402), and live status. This is meaningful behavioral context beyond what the input schema provides, though it does not mention side effects or error conditions.
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 two sentences: the first lists the key analysis aspects and outputs, the second gives cost and status. Every sentence adds value, and it is front-loaded with the primary 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 simple one-parameter tool with no output schema, the description covers purpose, return fields, cost, and network. It does not explain the meaning of each output field, but that is a minor gap given the straightforward nature of 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?
Schema description coverage is 100% for the only parameter (address), which already includes a pattern and description. The tool description does not add new semantic information about the parameter, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Analyze a Base token for honeypot risk, taxes, liquidity and ownership.' It uses a specific verb and resource, and the listed analysis dimensions distinguish it from the sibling tools (analyze_holder_clusters, get_market_data).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for token safety checks but does not explicitly state when to use this tool versus alternatives, nor does it mention exclusions or prerequisites. It provides context ('Analyze a Base token') but lacks direct comparative guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_market_dataAInspect
Get real-time USD prices for Bitcoin, Ethereum, Solana, VIRTUAL, AERO and cbBTC. Cost: $0.002 USDC via x402. LIVE.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
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 cost ($0.002 USDC via x402) and the 'LIVE' nature of the data, which are useful behavioral traits. However, it does not describe the response format, possible errors, or any rate limits, leaving gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise and front-loaded with the core purpose. It consists of two sentences with no filler, efficiently conveying the action, the assets, and the cost.
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 (no parameters, no output schema), the description adequately covers the essential aspects: what it does, which assets, and the cost. However, it could be more complete by indicating the expected output shape or typical use cases, though these are not critical for a price-fetching 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 tool has zero parameters and the input schema is empty, so the baseline is 4. The description adds value by enumerating the specific assets covered, which clarifies the scope beyond the empty 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 clearly states a specific verb ('Get') and resource ('real-time USD prices') with an explicit list of covered assets. It does not explicitly distinguish from sibling tools, but those are named 'analyze_holder_clusters' and 'check_token_safety', which are clearly different in scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives, nor any exclusions or prerequisites. The description implies its use for fetching current prices, but offers no explicit context or comparison to sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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Glama MCP Gateway
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TDQS
Each tool targets a distinct purpose: market data, token safety, and holder cluster analysis. There is no overlap in functionality, making it easy for agents to select the correct tool.
All tools follow a consistent verb_noun pattern with lowercase snake_case (analyze_, check_, get_). This creates a predictable naming convention.
With only 3 tools, the server is on the lower end of typical counts, but each tool is distinct and serves a specific financial analysis function. The count is slightly thin but not inappropriate.
The server only provides three functions, with two not yet live. Significant gaps exist, such as no tool for token price, trading history, or portfolio management, making the surface incomplete for comprehensive finance analytics.