painspotter
Server Details
AI-analyzed startup opportunities from Reddit, Hacker News & Product Hunt, with commercial scores.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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.
Tool Definition Quality
Average 4/5 across 5 of 5 tools scored.
Each tool has a clear, distinct purpose: overview, theme listing, theme detail, opportunity query, opportunity detail. No two tools overlap in functionality; descriptions clearly differentiate them.
All tool names follow a consistent verb_noun pattern (get_*, list_*, query_*). The naming is uniform and predictable, making it easy for an agent to infer function.
With 5 tools, the surface is well-scoped for exploring market signals and opportunities. Each tool earns its place, covering high-level overview, theme browsing, and detailed opportunity queries without excess.
The toolset provides a complete read-only exploration workflow for themes and opportunities. A minor gap is the lack of a dedicated tool for category/domain details beyond the overview, but the overview already provides sufficient summary information.
Available Tools
5 toolsget_opportunityGet Opportunity DetailARead-onlyIdempotentInspect
Get the full detail of a specific opportunity: description, score breakdown, MVP features, competitors, differentiation, risks and community evidence count. (Free tool)
| Name | Required | Description | Default |
|---|---|---|---|
| opportunity_id | Yes | Opportunity ID, taken from query_opportunities or get_overview results. |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. It implies a read operation (获取详情) and notes it's a free tool, but does not explicitly state idempotency, safety, rate limits, or authentication needs. The description is mostly clear but lacks explicit behavioral guarantees.
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 concise with two primary sentences plus an Args section. It front-loads the purpose and key details, and every sentence serves a clear function. No extraneous content.
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 1 required parameter, the existence of an output schema (so return values need not be explained), and low complexity (no nested objects, no enums), the description is complete. It covers what the tool does, what it returns, and where to get the input.
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 input schema only defines 'opportunity_id' as an integer with 0% description coverage. The description adds meaning by specifying the ID originates from query_opportunities or get_overview, which is valuable context beyond the schema. However, it does not elaborate on parameter format or validation rules.
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 explicitly states it retrieves complete details for a specific opportunity, listing all included fields (描述、评分明细、MVP 功能、竞争对手、差异化、风险点、社区证据数). This clearly differentiates it from siblings like query_opportunities (which likely lists opportunities) and get_overview. The verb '获取' (get) combined with the resource '指定商机' (specified opportunity) makes the action unambiguous.
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 a clear usage guideline: the opportunity_id must come from query_opportunities or get_overview results. This informs the agent about the required prior context. However, it does not explicitly state when not to use this tool or compare with alternatives beyond the one line.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_overviewGet OverviewARead-onlyIdempotentInspect
Get a global overview of PainSpotter: all domain categories (with theme count, opportunity count and 30-day mentions) plus a snapshot of currently trending themes. A good first step to map the landscape before drilling in with the other tools. (Free tool)
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Details the returned data (domain classifications with counts, trending themes). Without annotations, description carries full burden; it adequately discloses output but does not explicitly state it is read-only or non-destructive. 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?
Two concise sentences plus a parenthetical. Front-loaded with main action, no wasted words. Every 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 zero parameters, presence of output schema, and no annotations, description fully covers purpose, use case, and return data. Complete for a summary/overview 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?
No parameters (0 params, 100% schema coverage). Description adds value by explaining that the overview includes domain classifications, counts, and trending themes—context beyond schema. Baseline 4 for zero-parameter tools.
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 retrieves a global overview with domain classifications (topic/opportunity counts, 30-day discussion volume) and trending themes. Verb '获取' plus specific resource '全局总览' make purpose unmistakable, and it distinguishes itself from sibling tools by positioning as an entry point.
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 says '适合作为探索的第一步' (suitable as first exploration step) and directs to use other tools for deeper dives. Also notes it's a free tool, providing clear when-to-use guidance and context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_themeGet Theme DetailARead-onlyIdempotentInspect
Get the full market signal for a single theme: trend, 30-day / all-time mentions, signal channels, audience clarity and market summary, plus the top-scoring opportunities under it (including the Best Bet flagship opportunity). (Pro tool)
| Name | Required | Description | Default |
|---|---|---|---|
| theme | Yes | Theme ID (numeric) or slug (string), from list_trending_themes / get_overview. |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description does not disclose behavioral traits such as read-only, auth requirements, rate limits, or side effects. It only lists outputs, leaving the agent uninformed about operational characteristics.
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 concise and contains all necessary info in a single block, but the bullet-style list could be better formatted for readability. Front-loads the main purpose effectively.
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 existence of an output schema, the description sufficiently covers the tool's functionality and parameter source. However, it omits potential error cases, authentication needs, or Pro-tier usage details, leaving minor gaps.
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 1 parameter with no description, but the description clarifies that theme can be a numeric ID or slug string and states it comes from specific sources. This adds significant meaning beyond the schema, though it could benefit from format examples.
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 explicitly states the tool retrieves comprehensive market signals for a single theme, including trends, discussion volumes, signal channels, audience clarity, market summary, and top opportunities. It clearly differentiates from siblings by specifying it's for a single theme and includes the best opportunities with Best Bet.
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?
Description mentions the input comes from list_trending_themes/get_overview, implying context, but does not explicitly state when to use this tool versus alternatives like get_opportunity or list_trending_themes. No guidance on when not to use or prerequisite conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_trending_themesList Trending ThemesARead-onlyIdempotentInspect
List themes that are currently heating up (sorted by trend change %), to catch demand that is growing. A theme is the "market-signal layer": it aggregates multiple opportunities and carries 30-day mentions, trend direction and audience clarity. (Pro tool)
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Number of themes to return, 1-30. Default 15. | |
| min_mentions | No | Minimum 30-day discussion count, filters out noise. Default 2. |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavior. It explains the output fields (30-day mentions, trend change, audience clarity) and sorting. However, it does not mention authentication, rate limits, or potential costs. For a read-only list tool, the transparency is adequate but could be more thorough.
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 relatively concise, with a clear lead sentence and an organized Args section. It avoids unnecessary detail. Slightly longer due to bilingual text but still efficient.
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 exists, the description doesn't need to detail return values. It explains what themes are and their included fields. However, it lacks guidance on handling results and when to use this tool over siblings. For a simple tool, it's reasonably complete but not fully.
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 input schema has no descriptions (0% coverage), so the description must compensate. It includes an Args section that explains 'limit' (1-30, default 15) and 'min_mentions' (minimum 30-day mentions, default 2), adding meaning beyond the schema. This effectively guides parameter usage.
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 lists trending themes sorted by trend change percentage descending. It specifies the resource (themes) and the action (list trending). However, it does not explicitly differentiate from sibling tools like 'get_theme' or 'query_opportunities', so it loses some clarity.
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 the tool is for identifying growing demand via themes that aggregate multiple opportunities. It notes it's a Pro tool but provides no explicit guidance on when to use or not use this tool compared to alternatives. Usage context is implied but not fully explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
query_opportunitiesQuery OpportunitiesARead-onlyIdempotentInspect
Unified opportunity search: filter by keyword, minimum score, platform, recommendation tier and domain category, then sort the results. (Pro tool)
| Name | Required | Description | Default |
|---|---|---|---|
| sort | No | Sort order: 'score' (default, by overall score) or 'recent' (by creation time). | score |
| query | No | Keyword matched against title + description, e.g. "sleep tracker", "AI writing". Empty = no keyword filter. | |
| category | No | Category slug from get_overview, e.g. ai-developer-tools. Empty = all categories. | |
| platform | No | Platform filter: reddit / hackernews / producthunt / stackexchange. Empty = all platforms. | |
| min_score | No | Minimum overall score, 0-100. Default 0. | |
| page_size | No | Number of results to return, 1-30. Default 10. | |
| recommendation | No | Recommendation tier: Build / Validate / Skip. Empty = all tiers. |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry full behavioral disclosure. It only describes parameters and default values, omitting details like what the tool returns (list of opportunities), side effects, authentication requirements, or rate limits. The mention of 'Pro 工具' hints at access control but is insufficient.
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 concise and well-structured: a one-line purpose followed by a bullet list of arguments. Each argument is explained in a clear, parallel format. No redundant or extraneous information.
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 7 optional parameters and the existence of an output schema, the description covers all inputs adequately. It mentions the source for category slugs (get_overview). However, it does not explicitly state that the return is a list of opportunities or that this is a 'Pro' tool requiring subscription. Minor gaps.
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, the description compensates fully by explaining each parameter's meaning, valid values, and examples. It clarifies defaults and provides context like '留空=不限' (leave blank for unlimited) and cross-references category slugs to get_overview.
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 '统一商机查询' (unified opportunity query) and lists all filtering and sorting parameters. It distinguishes itself from sibling tools like get_opportunity (singular retrieval) and get_overview (summary) by emphasizing its role as a multi-dimensional query tool.
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 querying opportunities with filters but does not explicitly mention when to use this tool versus siblings (e.g., get_opportunity for single item, get_overview for categories). It lacks when-not or alternative guidance.
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.
Discussions
No comments yet. Be the first to start the discussion!