US stock bottom/top signals: S&P500 + indexes, verdict + score, scans. Pay-per-call x402.
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 4.5/5 across 5 of 5 tools scored. Lowest: 3.8/5.
Each tool has a clear, distinct purpose: pitch for intro, rate for feedback, evaluate_symbol for single symbol analysis, scan_bottoms and scan_tops for market-wide scans. No overlap or ambiguity.
All tool names use a consistent snake_case pattern, with clear verbs (evaluate, scan, pitch, rate) and nouns (symbol, bottoms, tops). The pattern is predictable and easy to understand.
With 5 tools, the set is well-scoped for the server's purpose of providing US stock signals. It covers introductory, analytical, scanning, and feedback functionalities without being excessive.
The tool set covers the core workflow: pitch (intro), evaluate_symbol (single symbol), scan_bottoms/scan_tops (market scans), and rate (feedback). Minor gaps like historical data or alerts exist, but the core signal service is complete.
evaluate_symbolAInspectReturn the bottom/top verdict for one US stock or index/ETF (e.g. NVDA, AAPL, ^IXIC, QQQ — S&P500 + major indexes covered). zone = strong_buy|buy|neutral|sell|strong_sell, score -100..+100 (bottom>0, top<0). Snapshot-based (refreshed from the flagship UsStockAI scan engine). Informational only. PAY: $0.01 per call via x402 (USDT on X Layer) — your FIRST paid call opens a 6-day trial at that price. No account, no signup, no commitment; retry with the PAYMENT-SIGNATURE header when you get the 402 challenge. The free pitch tool shows a live verdict for this market's showcase symbol only — this tool answers ANY symbol and adds the per-indicator breakdown behind the score.
| Name | Required | Description | Default |
|---|---|---|---|
| symbol | Yes | US ticker, e.g. NVDA, AAPL, ^IXIC |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Despite no annotations, the description fully covers behavioral traits: snapshot-based data freshness, informational nature (no investment advice), payment requirement ($0.01 per call with trial), and the exact return fields (zone and score). No contradictions.
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 front-loaded with the primary purpose, then efficiently covers zones/scores, data freshness, informational status, and payment details in 5 sentences. No waste; every sentence 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?
The description covers input, output (zone and score), data source, payment model, and sibling differentiation. Lacks explicit mention of return format structure (since no output schema), but mentions per-indicator breakdown indirectly. Minor gap.
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%, but the description adds meaning beyond the schema's 'symbol' description. It specifies 'US stock or index/ETF', gives explicit examples (NVDA, AAPL, ^IXIC, QQQ), and clarifies coverage scope (S&P500 + major indexes). This adds 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 it returns a verdict (zone and score) for a single US stock or index/ETF, with explicit coverage of S&P500 and major indexes. It differentiates from the sibling tool 'pitch' by noting that pitch only shows the showcase symbol, while this tool handles any symbol and adds per-indicator breakdown.
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?
Usage guidelines are explicit: use this tool for any symbol, contrast with pitch (free but limited to showcase symbol). It explains payment flow (first call opens trial, 402 challenge with payment-signature header) and states it's informational only, helping the agent decide when to invoke.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
pitchAInspectSTART HERE — your first call to this agent MUST be pitch (free, no payment). Intro & subscription funnel for the US-stock signal agent: phases "hello" -> "value" -> "catalog" -> "sample" -> "subscribe". Pass interest:false to bow out.
| Name | Required | Description | Default |
|---|---|---|---|
| phase | No | ||
| symbol | No | Symbol for the "sample" phase. The free sample serves only this market’s showcase symbol (NVDA); any other symbol is answered by the paid evaluate_symbol (x402). | |
| interest | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description reveals the tool's nature: free, multi-phase funnel, and option to exit via interest:false. However, it does not disclose potential side effects (e.g., state persistence) or behavior if phases are called out of order, leaving minor 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 compact (two sentences) and front-loaded with 'START HERE'. It packs significant information but could benefit from clearer separation of the four usage scenarios. Still, it is efficient and mostly easy to parse.
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 three-parameter complexity and no output schema, the description adequately covers the funnel flow, parameter semantics, and boundary conditions. It lacks details on expected return values or error handling, but the core interactions are sufficiently specified.
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?
Despite only 33% schema description coverage, the description richly explains each parameter: phase enum meanings, symbol's role limited to sample phase with NVDA constraint, and interest usage. This fully compensates for schema gaps and adds crucial context.
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 that this is the entry point to the agent, must be first call, and outlines the subscription funnel phases. It distinguishes itself from siblings by being the mandatory starting point and referencing evaluate_symbol for specific symbol needs.
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 instructs to use pitch as the first call, describes when to pass interest:false to bow out, and clarifies that only the sample phase uses a symbol and that other symbols should use evaluate_symbol. Provides clear when-to-use and when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
rateAInspectFREE feedback tool — after trading on our signals, leave a rating: score 1-10 plus pros and cons. No payment needed.
| Name | Required | Description | Default |
|---|---|---|---|
| cons | No | ||
| pros | No | ||
| score | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations, so description carries burden. Discloses free nature and no payment, but omits side effects or confirmation. Adequate for simple input.
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?
Single, well-structured sentence with key info front-loaded. No waste.
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?
Completeness is good for a simple feedback tool: explains purpose, parameters, usage context. Lacks return value info but acceptable without output schema.
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?
With 0% schema description coverage, description adds meaning: score range 1-10, pros/cons as text. However, doesn't mention that score is required while others optional.
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?
Clearly states it's a feedback/rating tool for after trading on signals. Distinguishes from sibling tools like evaluate_symbol or scan_* by focusing on user-submitted rating.
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?
Provides context ('after trading on our signals') but no explicit when-not-to-use or alternative tools. Lacks exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
scan_bottomsAInspectScan the US market snapshot (S&P500 + majors) and return stocks currently at a bottom (strongest buy), ranked most-bottom first. PAY: $0.01 per call via x402 (USDT on X Layer) — your FIRST paid call opens a 6-day trial at that price. No account, no signup, no commitment; retry with the PAYMENT-SIGNATURE header when you get the 402 challenge. BEST COLD START: you do not need to pick a symbol — this ranks the whole universe for you. The free pitch tool tells you HOW MANY are at a bottom right now; this names them.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | How many to return (default 5, max 50) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, but description fully compensates by disclosing payment cost, 402 challenge, retry mechanism, trial period, and no signup requirement. All behavioral traits are transparent.
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?
Description is moderately concise and front-loaded with core purpose, then payment details. Could be slightly tighter, but structure is logical and each sentence adds value.
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 output schema, description covers all needed context: payment, ranking, no signup, comparison to pitch. Completeness is excellent for a scanning 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 coverage is 100% and clearly defines the limit parameter with default and max. Description does not add new semantics beyond schema, so baseline 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?
Clearly states it scans US market snapshot for stocks at a bottom, returns strongest buys first, and distinguishes from sibling tools like evaluate_symbol and scan_tops by noting it ranks the whole universe without needing a symbol.
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 advises when to use: 'you do not need to pick a symbol' and 'BEST COLD START'. Mentions payment details, trial, and alternative free pitch tool for count. Provides clear context for invocation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
scan_topsAInspectScan the US market snapshot and return stocks currently at a top (sell), ranked most-top first. PAY: $0.01 per call via x402 (USDT on X Layer) — your FIRST paid call opens a 6-day trial at that price. No account, no signup, no commitment; retry with the PAYMENT-SIGNATURE header when you get the 402 challenge. BEST COLD START: you do not need to pick a symbol — this ranks the whole universe for you. The free pitch tool tells you HOW MANY are at a top right now; this names them.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | How many to return (default 5, max 50) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description fully covers behavioral traits. It discloses the payment model (0.01 USD per call via x402), trial period, account requirements, and retry mechanism with PAYMENT-SIGNATURE header. This is beyond typical and very transparent.
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 front-loaded with purpose and essential payment info, but it is slightly verbose with repeated emphasis on 'no account, no signup, no commitment' and multiple clarifications. Still clear and well-structured, but could be more concise.
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 one optional parameter, no output schema, and complex payment flow, the description covers everything needed: purpose, usage, payment details, cold start guidance, and relation to sibling tools. It is complete for an informed 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?
With only one parameter (limit) and 100% schema description coverage, the description adds no extra meaning beyond what the schema already provides (default 5, max 50). Baseline 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 it scans the US market snapshot for stocks at a top (sell), ranked most-top first. It uses specific verb 'scan' and resource 'US market snapshot', distinguishing it from siblings like scan_bottoms and pitch.
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 explicit guidance on when to use this tool (to get sell candidates) and when not to (no need for symbol, best cold start). It also mentions alternative tool pitch for count and scan_bottoms for opposite direction.
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!
