247 LLMs + image/video/voice/music gen + crypto/DeFi/markets/web-search. Pay-per-call USDC, no key.
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 4.3/5 across 5 of 5 tools scored. Lowest: 3.7/5.
Each tool has a clearly distinct purpose: installation snippets, endpoint listing, pricing, usage stats, and wallet setup. No overlap or ambiguity.
All tool names follow a consistent verb_noun pattern in snake_case, making them predictable and easy to understand.
With 5 tools, the set is well-scoped for an agent tools gateway, covering all essential discovery, setup, and payment tasks without being too few or too many.
The tool set covers the full lifecycle: installation, endpoint discovery, pricing, usage monitoring, and payment setup. No obvious gaps for the gateway purpose.
install_snippetsAInspectReturn ready-to-paste configuration snippets for installing this MCP server in Claude Code, Cursor, Cline, Continue.dev, Windsurf, and Zed. Free.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description bears full responsibility. It mentions 'free' but fails to disclose other behavioral traits like idempotency, side effects, or required authentication. The minimal disclosure leaves uncertainty about the tool's safety and side effects.
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 unnecessary words. It conveys the essential information efficiently.
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 simplicity of the tool (no parameters, simple return of text snippets), the description is fully complete. It explains what the tool returns and for which targets. No output schema is needed to understand the return value.
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 schema coverage is effectively 100%. Following the guideline for 0 parameters, baseline is 4. No parameter information is needed, and the description does not add any param semantics, which 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 returns ready-to-paste configuration snippets for installing the MCP server in multiple environments (Claude Code, Cursor, etc.). It uses a specific verb+resource and effectively distinguishes itself from sibling tools like 'pricing_info' or 'usage_stats'.
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 on when to use this tool versus alternatives. The description only states what it does, without mentioning prerequisites, typical scenarios, or exclusions. Sibling tools are listed but no explicit comparison is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_endpointsAInspectList all paid endpoints exposed by this MCP server with their prices and live status. Free — no wallet required. Use this first to discover what tools are available.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It discloses the tool is free and requires no wallet, but lacks details on data freshness or completeness of the list.
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 clear front-loading of purpose, then key info (free, no wallet), then usage guidance. No superfluous 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?
Adequate for a simple zero-param tool. Covers purpose, cost, and usage order. Could mention whether the list is exhaustive or includes free endpoints.
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?
Zero parameters with 100% schema coverage. Baseline is 4, and description adds no parameter info, which 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?
Description clearly states it lists paid endpoints with prices and live status. It explicitly positions itself as a discovery tool ('Use this first'), distinguishing it from sibling tools like pricing_info or install_snippets.
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?
Explicitly states 'Free — no wallet required' and 'Use this first to discover what tools are available,' giving clear when-to-use guidance and positioning it before other tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
pricing_infoAInspectReturn pricing details for the GoCreative Agent API — base price per call, premium endpoints, cache TTLs, and supported payment networks. Free.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It states it returns data and is free, but doesn't explicitly mention side effects, authentication, or rate limits. For a read-only tool, this is adequate but could be improved.
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 that front-loads the main action and lists key details without waste. Every word is purposeful.
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 no parameters and no output schema, the description provides sufficient context: it names specific data points returned (base price, premium endpoints, cache TTLs, payment networks) and notes it's free. This covers the tool's functionality completely for a simple info retrieval 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, so the baseline is 4. The description doesn't need to add parameter meaning beyond the schema, and it doesn't attempt to.
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 it returns pricing details for the GoCreative Agent API, listing specific items (base price, premium endpoints, cache TTLs, payment networks) and noting it's free. This distinguishes it from sibling tools like list_endpoints or usage_stats.
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?
While no explicit 'when to use' or 'when not to use' is given, the tool's purpose is straightforward and clearly differentiated from siblings by name and description. An agent can infer it's for retrieving pricing information, not for filtering or other operations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
usage_statsAInspectReturn summary stats of how this MCP server has been used (top tools called, success rate, recent activity). Free. Use to verify your own integration is hitting the right tools.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the burden. It mentions 'Free' and 'summary stats,' indicating read-only access, but lacks details on rate limits, data freshness, or authentication requirements. Adequate but not exhaustive.
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 concise sentences. The first clearly defines the output, the second provides practical usage guidance. Every phrase adds value, with no wasted 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 tool's simplicity (zero parameters, no output schema), the description adequately covers what is returned and how to use it. It could mention whether stats are live or cached, but overall is complete enough for an agent.
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 no parameters, so the description does not need to add meaning beyond the schema. Baseline 4 is appropriate since schema coverage is 100% and the description focuses on output rather than inputs.
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 it returns summary stats of MCP server usage, listing specific metrics (top tools called, success rate, recent activity). It distinguishes itself from siblings like install_snippets or pricing_info by focusing on usage analytics.
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 advises use for 'verifying your own integration is hitting the right tools,' providing a clear context. It does not mention when not to use or list alternatives, but the guidance is sufficient for typical scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
wallet_helperAInspectReturn step-by-step instructions for setting up x402 USDC autopay for this MCP server. Use this if a paid tool returned a 402 error or you're onboarding a new agent that needs to pay for API calls. Free.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. It clearly states it returns instructions and is free. No hidden side effects; behavior is straightforward for a guidance 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?
Two sentences, no wasted words. Front-loaded with core function and usage 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?
Given no parameters and no output schema, the description provides complete guidance for an agent to use the tool appropriately.
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 has 0 parameters with 100% coverage; description adds no parameter info as none needed. Baseline 4 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?
Description specifies the verb 'return' and the resource 'step-by-step instructions for setting up x402 USDC autopay', clearly stating what the tool does. It also distinguishes itself from siblings by focusing on payment setup, not installation or listing.
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?
Explicitly states when to use: 'if a paid tool returned a 402 error or you're onboarding a new agent'. Also marks as 'Free', guiding cost-avoidance.
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.
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