One-to-three-cent spend routing, lead research, token-risk, and agent-tool comparison preflights.
Glama MCP Gateway
Connect through Glama MCP Gateway for full control over tool access and complete visibility into every call.
Full call logging
Every tool call is logged with complete inputs and outputs, so you can debug issues and audit what your agents are doing.
Tool access control
Enable or disable individual tools per connector, so you decide what your agents can and cannot do.
Managed credentials
Glama handles OAuth flows, token storage, and automatic rotation, so credentials never expire on your clients.
Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Average 4.2/5 across 4 of 4 tools scored.
Tools are mostly distinct: compare tool options, generate lead brief, quote agent route, and score token risk. However, 'compare_market_tool_options' and 'quote_agent_route' both involve tool selection and cost, which could cause some confusion.
All tool names follow a consistent verb_noun snake_case pattern: compare_, generate_, quote_, score_. This makes the set predictable and easy to navigate.
With 4 tools, the server is well-scoped for its purpose of providing decision-support for paid tool usage. Each tool addresses a specific aspect of that domain without being excessive or too thin.
The domain appears to be agentic decision-support for market/lead/tool/token evaluation. Core workflows are covered, but there is no tool for actually executing purchases or managing subscriptions, which could be a minor gap.
compare_market_tool_optionsMarket Tool ComparisonACompare a task against public xpay catalog options and observed high-demand tool patterns before an agent chains several paid tools. Returns competing tool surfaces, Signal Desk countermoves, moat guidance, unsupported claims, and recommended next paid calls. Buy and run for 0.03 USDC on Base at https://payanagent.com/x402/kh79rcw8zvdhssthrvbwa32rtd8ahzww.
| Name | Required | Description | Default |
|---|---|---|---|
| task | Yes | Plain-language task, market, or toolchain decision the agent is about to make. | |
| catalog | No | Optional caller-supplied xpay agents.txt-shaped catalog for deterministic or offline comparison. | |
| category | No | Optional xpay category to focus. Defaults to auto. | |
| max_options | No | Maximum competing tools to return, 1-10. Defaults to 6. |
| Name | Required | Description |
|---|---|---|
| source | Yes | |
| product | Yes | |
| priceUsd | Yes | |
| claimBoundary | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, indicating safe read-only behavior. The description adds valuable context: the cost (0.03 USDC), payment URL, and the specific return types (competing tool surfaces, Signal Desk countermoves, moat guidance, unsupported claims, recommended next paid calls). No contradiction with annotations.
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 states purpose and usage context; the second states return values and cost/payment details. It is front-loaded, concise, and every sentence serves a 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?
Given the output schema, annotations, and sibling context, the description provides sufficient information for an agent to decide when and how to use the tool. It covers purpose, usage timing, cost, and return contents, making it complete for this moderate-complexity 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%, with all four parameters fully described in the input schema. The description itself does not add parameter-specific details beyond what is in the schema, so the baseline of 3 applies. It does implicitly reference the 'task' parameter but adds no extra semantic value.
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 ('Compare') and resource ('public xpay catalog options and observed high-demand tool patterns'), along with the context ('before an agent chains several paid tools'). It distinguishes itself from sibling tools like quote_agent_route and score_defi_token_risk.
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 explicitly indicates when to use the tool: 'before an agent chains several paid tools.' It provides clear context but does not explicitly mention when not to use it or name alternative tools. However, the differentiation from siblings is clear through the purpose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
generate_public_lead_briefPublic Lead BriefAFetch a public website and return a buyer-fit brief with public signals, agentic offer angles, and next actions. No private contact database is queried. Buy and run for 0.03 USDC on Base at https://payanagent.com/x402/kh7b6yxnq209169aq8wavbqzh98ag9gv.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Public website URL or domain to inspect. | |
| company | No | Optional company name override. | |
| target_buyer | No | Optional target buyer/audience. |
| Name | Required | Description |
|---|---|---|
| source | Yes | |
| product | Yes | |
| priceUsd | Yes | |
| claimBoundary | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, openWorld, idempotent, and non-destructive hints. The description adds useful behavioral context beyond annotations: it explicitly states that no private contact database is queried and includes execution/payment details (0.03 USDC, Base network, URL). This adds transparency without contradicting any annotations.
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, front-loaded with the core action, and every sentence earns its place. The first sentence explains what the tool does; the second adds a key limitation and the payment/execution link. No redundant words.
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 rich annotations and existing output schema, the description completely covers the tool's purpose, behavior, and execution details. It explains the returned brief's components and the cost/network, leaving no missing context that would impair an agent's decision to invoke it.
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%, so all three parameters are already described in the input schema. The description does not add further parameter-specific guidance, but it indirectly clarifies the 'url' parameter by saying 'Fetch a public website'. This matches the baseline of 3 for full schema coverage.
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 verb ('Fetch') and resource ('a public website') and specifies the output ('a buyer-fit brief with public signals, agentic offer angles, and next actions'). It also distinguishes itself from siblings by focusing on public lead generation rather than market comparison, agent routes, or DeFi risk scoring.
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 use (public website input, lead brief output) and implicitly notes a limitation ('No private contact database is queried'), suggesting when NOT to use it. However, it does not explicitly name alternative tools or state when to prefer them, so it lacks the full 'when/when-not' guidance of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
quote_agent_routeAgent Route QuoteAEstimate the cheapest sensible agent execution lane before buying model calls or xpay tools. Returns a budget decision, tool-stack recommendation, and fallback plan. Buy and run for 0.03 USDC on Base at https://payanagent.com/x402/kh732rk76r7nv67q1h5223kc9x8agkfx.
| Name | Required | Description | Default |
|---|---|---|---|
| task | Yes | Plain-language task, goal, or prompt the agent is about to run. | |
| needs_code | No | ||
| needs_onchain | No | ||
| max_budget_usd | No | Maximum total budget for the task. Defaults to 0.25. | |
| needs_contacts | No | ||
| risk_tolerance | No | How conservative the route should be. | |
| needs_current_web | No | ||
| latency_preference | No | Preferred speed/quality tradeoff. |
| Name | Required | Description |
|---|---|---|
| source | Yes | |
| product | Yes | |
| priceUsd | Yes | |
| claimBoundary | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare the tool as read-only, open-world, idempotent, and non-destructive. The description adds valuable context about the tool's return structure (budget decision, tool-stack recommendation, fallback plan) and references a payment URL/cost, which is relevant for understanding the execution workflow. No contradiction with annotations.
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, front-loaded with the primary purpose, followed by the return summary and payment linkage. It is concise and efficient, with no filler or redundant information that duplicates structured data.
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 presence of an output schema, the description does not need to detail return values. It covers the use case, output summary, and cost/payment angle. The main gap is the lack of parameter explanation, but the schema provides parameter names and some descriptions. Overall, the description is sufficiently complete for a quoting tool with annotations.
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 description coverage is 50%, with four parameters (needs_code, needs_onchain, needs_contacts, needs_current_web) lacking descriptions. The tool description does not compensate by explaining what these parameters mean or how they affect the quote. It relies solely on parameter names, which are not self-explanatory for all cases. The description adds no semantic value 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 clearly states the tool's purpose with a specific verb ('Estimate') and resource ('cheapest sensible agent execution lane'), and enumerates the output types: budget decision, tool-stack recommendation, and fallback plan. It distinguishes itself from sibling tools like compare_market_tool_options and score_defi_token_risk by focusing on pre-purchase routing and cost estimation.
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 clear context for when to use the tool: 'before buying model calls or xpay tools'. This implies it is for pre-purchase planning. It does not explicitly enumerate when not to use it or name alternative tools, but the context is unambiguous enough to guide selection among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
score_defi_token_riskDeFi Token Risk SnapshotAReturn a research-only token risk snapshot from public liquidity, volume, pair-age, volatility, and data availability. Does not trade and is not financial advice. Buy and run for 0.01 USDC on Base at https://payanagent.com/x402/kh7eqsawc4t694gf1pxqn5shwn8ah5sw.
| Name | Required | Description | Default |
|---|---|---|---|
| chain | No | ||
| market_data | No | Optional caller-supplied Dexscreener-shaped data for deterministic/test usage. | |
| token_address | Yes | EVM token address or Solana mint address. |
| Name | Required | Description |
|---|---|---|
| source | Yes | |
| product | Yes | |
| priceUsd | Yes | |
| claimBoundary | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false. The description adds beyond that by stating 'Does not trade' and 'not financial advice,' and reveals a 0.01 USDC payment requirement via a URL. These are useful behavioral and cost details that do not contradict the annotations.
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 three sentences: purpose, safety caveat, and payment instruction. The function is front-loaded and there is no filler, but the URL and payment sentence adds operational detail that could be considered slightly extraneous to the core description.
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?
An output schema exists, so return values are documented externally. The description covers data sources, payment, and non-trading behavior, which is adequate for a read-only snapshot tool. It could mention required token_address or chain behavior, but those are handled by the schema, so no major gaps remain.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description does not elaborate on the individual parameters. The schema already covers token_address and market_data with descriptions and chain via an enum, giving 67% coverage. The description adds no extra meaning for parameters, so a baseline score 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 opens with 'Return a research-only token risk snapshot from public liquidity, volume, pair-age, volatility, and data availability,' which is a specific verb+resource statement and clearly lists the data inputs. It distinguishes the tool from siblings like compare_market_tool_options and quote_agent_route by focusing on a risk snapshot rather than market comparison or quoting.
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 clear when-not context ('Does not trade and is not financial advice') and labels the tool as 'research-only,' which implies appropriate use cases. It also discloses a payment prerequisite ('Buy and run for 0.01 USDC on Base'), but it does not name alternatives or explicitly state when to prefer 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.
Claim this connector by publishing a /.well-known/glama.json file on your server's domain with the following structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
}The email address must match the email associated with your Glama account. Once published, Glama will automatically detect and verify the file within a few minutes.
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
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.
No comments yet. Be the first to start the discussion!
Sign in to create a connector for this server.