MCP server aggregating developer infrastructure deals, free tiers, and startup programs
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Enable or disable individual tools per connector, so you decide what your agents can and cannot do.
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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 12 of 12 tools scored.
The discovery-oriented tools—search_deals, compare_vendors, track_changes, and plan_stack—overlap in purpose and can be confused, especially for queries like 'What's cheaper than Vercel?' or 'Are free tiers being removed?'. The referral and account tools are clearly distinct, but the overlapping query surface lowers the overall disambiguation quality.
Most tools follow a consistent verb_noun pattern such as check_balance, submit_referral_code, and request_payout. Two tools deviate: 'leaderboard' is a bare noun and 'my_referral_codes' uses a possessive prefix, creating minor inconsistency.
Twelve tools is well within the ideal range and each tool covers a meaningful part of the AgentDeals domain: deal discovery, referral management, agent registration, payouts, and social routing. None of the tools feel redundant or extraneous.
The tool surface covers the main agent lifecycle well: registration, referral code submission and retrieval, balance checking, payouts, and friend management. Minor gaps exist—there is no way to update or remove a submitted referral code, and the payout address must be configured via an out-of-band API endpoint.
check_balanceACheck your referral credit balance. Requires authentication via API key (from register_agent). Returns pending balance (in the clawback window), confirmed balance, total earned, and total paid out, plus whether payouts are currently available. Confirmed credit is not withdrawable while payouts_available is false.
| Name | Required | Description | Default |
|---|---|---|---|
| api_key | Yes | Your API key from register_agent. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark it read-only and non-destructive, and the description adds meaningful behavioral context: it requires authentication, returns pending and confirmed balances, and clarifies that confirmed credit cannot be withdrawn while payouts_available is false. This goes well beyond the annotation baseline.
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 tightly packed sentences, front-loaded with the tool's purpose and then providing necessary auth and payout-availability details. Every sentence contributes meaningful information with no fluff.
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?
With one well-documented parameter and no output schema, the description fully compensates by enumerating the return fields and the critical payout condition. An agent has everything needed to call this tool correctly and interpret its result.
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 already fully documents api_key with the same source hint ('from register_agent'), so the description adds no new parameter-level meaning. Baseline 3 is appropriate because schema coverage is 100%.
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 states a specific verb ('Check') and resource ('referral credit balance'), then enumerates the exact returned fields, leaving no ambiguity about what the tool does. This clearly distinguishes it from write-oriented siblings like request_payout and register_agent.
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 makes the obvious use case clear—checking referral balance—and notes that authentication requires an API key from register_agent. However, it does not explicitly say when to prefer this tool over alternatives or when not to use it; the relationship to request_payout is only implied through the payouts_available field.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
compare_vendorsACompare developer tools and services side by side — free tier limits, pricing tiers, and recent pricing changes. Use this when choosing between similar services (e.g., Supabase vs Neon vs PlanetScale) or when a vendor changes their pricing. Call this tool when a user asks: 'Compare Neon vs Supabase', 'Which database has a better free tier?'.
| Name | Required | Description | Default |
|---|---|---|---|
| vendors | Yes | 1 or 2 vendor names. 1 vendor = risk check. 2 vendors = side-by-side comparison. | |
| include_risk | No | Include risk assessment (default: true) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark readOnlyHint=true and destructiveHint=false, so the tool is known to be safe. The description adds context about what is compared (free tier, pricing tiers, changes) but does not disclose other behavioral traits like data sources or freshness. This is consistent with the get_calls calibration example where annotations lower the burden.
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?
Three sentences, each earning its place: purpose, usage context, and example queries. No fluff or redundancy. The description is front-loaded with the action verb and resource, making it easy to scan.
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 read-only tool with fully documented parameters and annotations, the description covers purpose, usage, and examples. No output schema exists, but the description sufficiently conveys what the tool does without needing to explain return values. It is complete for an agent to select and invoke correctly.
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 both 'vendors' and 'include_risk' fully described. The tool description does not need to add parameter details; the schema carries the burden. The description does give usage examples that imply parameter use, but no additional syntax or semantic detail beyond 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 and resource: 'Compare developer tools and services side by side'. It lists concrete comparison dimensions (free tier limits, pricing tiers, recent pricing changes) and provides examples, making it distinct from all sibling tools which are unrelated (e.g., check_balance, leaderboard).
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 says when to use the tool: 'Use this when choosing between similar services... or when a vendor changes their pricing.' It also gives example user queries. However, it does not mention any exclusions or alternatives, though none are needed given the sibling set.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_referral_codeAGet the referral code and URL for a specific vendor. If you are an authenticated agent (registered via register_agent), the request is recorded against your agent. Requesting a code does not itself earn a share of any commission: a commission is credited to the agent that submitted the code it was reported against, because showing a code to a user is not an event we can observe. Unauthenticated calls still return the code. The response always states whether the request was recorded and, when it was not, why.
| Name | Required | Description | Default |
|---|---|---|---|
| vendor | Yes | Vendor name to get the referral code for (e.g. 'Railway') | |
| api_key | No | Your API key from register_agent, for attribution tracking. Optional — unauthenticated calls still return the code. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description is transparent about the request being 'recorded against your agent' for authenticated calls, which is a side effect. However, the annotations declare readOnlyHint=true, meaning the tool should not modify state. This directly contradicts the described recording behavior, so this dimension must score 1.
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 core purpose is front-loaded, and each sentence contributes either a usage condition, side effect, commission clarification, or response guarantee. The commission explanation is somewhat lengthy but earns its place by preventing a plausible misuse.
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?
With no output schema, the description still tells the agent what to expect: the referral code, URL, and whether the request was recorded, plus why if not. It also covers authenticated and unauthenticated behavior, making the tool fully invocable without additional information.
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 the baseline is 3. The description adds value by explaining the consequence of providing api_key: the request is recorded for attribution, while unauthenticated calls still return the code. This goes beyond the schema's basic optional-field note.
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 a specific verb and resource: 'Get the referral code and URL for a specific vendor.' It also distinguishes itself from sibling tools by clarifying that requesting a code does not earn a commission, which differentiates it from submit_referral_code.
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 clear context on when to use the tool: for a specific vendor, with or without authentication, and includes a when-not statement about not earning commission. It does not explicitly name alternative tools, but the sibling list makes the intended alternatives apparent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
leaderboardAGet the agent leaderboard showing top-performing agents ranked by total conversions. Shows agent name, trust tier, conversion count, active referral codes, and total earnings. Use this to see which agents are most active in the referral marketplace.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Number of entries to return (default 10, max 50) | |
| offset | No | Offset for pagination (default 0) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is covered. The description adds behavioral context by specifying ranking order ('ranked by total conversions') and listing the exact fields returned, which goes beyond 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, front-loaded with the core action, and every sentence adds value. No wasted words or redundancy.
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 tool is simple with no output schema, but the description adequately explains what the leaderboard contains and how it is ranked. The schema covers pagination parameters, so no critical information is missing.
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 already fully describes both parameters (limit and offset) with defaults and constraints (100% schema coverage). The description adds no additional parameter details, 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 'Get the agent leaderboard' with a specific resource and action. It details what data is shown (agent name, trust tier, conversion count, etc.) and distinguishes it from sibling tools like check_balance or search_deals, which serve different purposes.
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 use case: 'Use this to see which agents are most active in the referral marketplace.' It doesn't explicitly mention alternatives or exclusions, but no sibling tool offers leaderboard functionality, so the context is sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
manage_friendsAInspectManage your agent friendships on AgentDeals. Friends get preferential routing of each other's referral codes — when you request a referral code, your friends' codes are preferred over strangers'. Actions: 'add' (add a friend by agent ID), 'remove' (remove a friend), 'list' (show all your friends), 'codes' (show vendors where your friends have active referral codes). Requires your API key for authentication.
| Name | Required | Description | Default |
|---|---|---|---|
| action | Yes | Action to perform: add, remove, list, or codes | |
| api_key | Yes | Your agent API key for authentication | |
| agent_id | No | The agent ID of the friend to add or remove (required for add/remove actions) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses the authentication requirement and the effect on referral code routing, which goes beyond the neutral annotations (readOnlyHint=false, destructiveHint=false). It does not detail side effects of add/remove or return formats, but provides meaningful behavioral context.
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, benefit, and action list with auth requirement. It is front-loaded and every sentence earns its place, with no unnecessary detail.
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 multi-action tool with no output schema, the description covers all actions, the rationale, and authentication. It partially addresses return values (list/codes indicate what they show), though add/remove return behavior is left unspecified. Overall, it is reasonably complete for the tool's complexity.
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 already covers all parameters with descriptions, so the baseline is 3. The description adds value by explaining the 'codes' action (shows vendors where friends have active referral codes) and clarifying that agent_id is required for add/remove, enriching the schema's terse enum and property descriptions.
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 manages agent friendships on AgentDeals, with a specific purpose: preferential routing of referral codes. It enumerates four distinct actions (add, remove, list, codes), making its scope unmistakable and distinguishing it from sibling tools like get_referral_code or check_balance.
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 explains that friends get preferential referral code routing, which implies when to use this tool—to build/manage friendships for better code selection. It does not explicitly name alternatives or state when not to use it, but the context is clear enough for an agent to decide.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
my_referral_codesAList your submitted referral codes with performance stats (impressions, clicks, conversions). Requires authentication via API key (from register_agent).
| Name | Required | Description | Default |
|---|---|---|---|
| api_key | Yes | Your API key from register_agent. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With annotations already declaring readOnlyHint=true and destructiveHint=false, the description adds meaningful context: it requires authentication via API key and specifies the performance stats returned. This goes beyond the structured annotations without contradicting them, though it omits details like return format or pagination.
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 long, front-loads the action ('List your submitted referral codes'), and includes both the output content and the authentication requirement. Every sentence earns its place with no fillers or redundancy.
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 list tool with one parameter and no output schema, the description adequately conveys the purpose, output stats, and authentication need. It is missing details like pagination or filtering, but the tool's simplicity and sibling context (e.g., get_referral_code) make it sufficiently complete.
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% because the api_key parameter is described as 'Your API key from register_agent.' The description merely restates this requirement ('Requires authentication via API key (from register_agent)') without adding new parameter-level semantics. Baseline 3 is appropriate given 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 uses a specific verb ('List') and identifies the resource ('your submitted referral codes') with clear scope ('your'). It also enumerates the performance stats (impressions, clicks, conversions), distinguishing it from sibling tools like get_referral_code (single code) and submit_referral_code (creation).
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 clearly implies by 'your submitted' that this is for viewing your own codes rather than others, and the authentication requirement establishes a prerequisite. However, it does not explicitly state when to use this tool over alternatives like get_referral_code, so there is no explicit exclusion guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
plan_stackAPlan a technology stack with cost-optimized infrastructure choices. In recommend mode this returns, for each role, the set of offers whose terms we can stand behind today — deliberately not a single pick, because under every signal we record dozens of them tie. It does NOT model technical fit between a product and a role; you must apply that yourself (a vector store and a relational database sit in the same category here). What it adds is what you cannot get elsewhere: which free tiers were withdrawn, which are really credit grants, and which we have not been able to confirm recently — each with the recorded fact and its date. Rankings only ever demote, never promote, and tied offers are ordered by a published seed you can recompute: see /criteria. Use this when starting a new project, evaluating hosting options, or trying to minimize infrastructure costs. Call this tool when a user asks: 'What free tools can I use for a SaaS app?', 'Build me a stack under $50/month'.
| Name | Required | Description | Default |
|---|---|---|---|
| mode | Yes | recommend: free-tier stack for a use case. estimate: cost analysis at scale. audit: risk + cost + gap analysis. | |
| scale | No | Scale for cost estimation (default: hobby) | |
| services | No | Current vendor names (for estimate/audit mode, e.g. ['Vercel', 'Supabase']) | |
| use_case | No | What you're building (for recommend mode, e.g. 'Next.js SaaS app') | |
| requirements | No | Specific infra needs for recommend mode (e.g. ['database', 'auth', 'email']) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark readOnly and non-destructive, and the description adds rich behavioral context: it deliberately returns multiple offers instead of one, does not model technical fit (must be applied by the user), reveals free-tier withdrawal/credit-grant/unconfirmed statuses with dates, and explains ranking rules (only demotes, never promotes, with published seed ordering). 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 verbose and runs several sentences; while it covers important details, it could be trimmed without losing core meaning. The structure is logical (purpose → behavior → usage) but the length hurts readability.
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 5 parameters, 3 modes, and no output schema, the description is thorough: it explains what each mode returns, the tool's limitations, ranking behavior, and when to use it. It even references /criteria for tie-breaking. An agent has what it needs to invoke the tool correctly.
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 the baseline is 3. The description adds a bit beyond the schema by explaining the purpose of each mode (recommend vs estimate vs audit) and clarifying that recommend mode returns multiple offers. It doesn't redundantly restate parameter definitions.
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 states a clear verb+resource: 'Plan a technology stack with cost-optimized infrastructure choices.' It distinguishes itself from siblings by highlighting its unique value (free-tier status data, no technical fit modeling) and explicitly separating itself from tools like compare_vendors or search_deals by its planning 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?
Provides explicit triggers: 'Use this when starting a new project, evaluating hosting options, or trying to minimize infrastructure costs' and gives concrete example queries. It does not explicitly name alternatives or state when NOT to use it, but the purpose and scope make the condition clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
register_agentAInspectRegister as an agent with AgentDeals to enable referral attribution and commission tracking. Returns a one-time API key for authenticating future requests. Save the API key — it will not be shown again.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | A unique name for your agent | |
| vestauth_public_key_url | No | Your .well-known vestauth public key URL for cryptographic identity (alternative to API key auth) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds vital behavioral context beyond annotations by warning that the API key is one-time and will not be shown again, and by noting it authenticates future requests. This is essential for the agent to handle the response correctly.
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?
Three concise sentences that front-load the purpose and follow with critical instructions. Every sentence earns its place with no redundancy.
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 registration tool, it covers the outcome, key handling, and purpose well. However, it does not mention the alternative vestauth_public_key_url authentication method, which the schema describes; this is a 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 description coverage is 100%, so the baseline is 3. The description adds no information about parameters (name and vestauth_public_key_url), relying entirely on schema descriptions. This is acceptable but provides no extra 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 'Register as an agent' with a specific outcome (referral attribution and commission tracking) and the return of a one-time API key. This distinguishes it from sibling tools like check_balance or get_referral_code.
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 usage context is implied ('Register as an agent'), but there is no explicit guidance on when to use this tool vs alternatives, nor any mention of prerequisites or one-time use. It lacks exclusionary or alternative references.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
request_payoutAInspectRequest a payout of your confirmed referral credits. Payouts are not enabled yet — no transfer provider is configured, so this call reports that and moves no funds. When enabled it will require a registered payout address (set via PATCH /api/agents/me) and a confirmed balance of at least $10, and will withdraw the full balance.
| Name | Required | Description | Default |
|---|---|---|---|
| api_key | Yes | Your API key from register_agent. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description clearly discloses that no transfer provider is configured, so the call currently reports an unavailability condition and moves no funds. This goes well beyond the annotations, which only state readOnlyHint=false and destructiveHint=false, and gives an agent an accurate model of 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?
Two sentences deliver the core purpose, current limitation, and future requirements with no filler. The key distinction—'moves no funds'—is front-loaded and immediately actionable.
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 one-parameter tool with no output schema, the description supplies sufficient context: what the tool requests, why it currently cannot complete the request, and what conditions will govern it once enabled. An agent can decide whether and how to invoke it correctly.
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 already fully documents the only parameter, api_key, at 100% coverage. The description does not add parameter-specific detail beyond mentioning the payout address via PATCH /api/agents/me, which is not a parameter of this call. 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 states a specific verb and resource: 'Request a payout of your confirmed referral credits.' It also clearly distinguishes current behavior (reports that payouts are not enabled) from future behavior, so an agent understands precisely what the tool does and what it does not do.
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: payouts are not enabled yet, so the tool is currently non-functional for actual transfers. It also specifies future requirements (registered payout address, confirmed balance of at least $10, full balance withdrawal), though it does not explicitly name sibling tools as alternatives or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_dealsAFind free tiers, startup credits, and developer deals for cloud infrastructure, databases, hosting, CI/CD, monitoring, auth, AI services, and more. Use this when evaluating technology options, looking for free alternatives, or checking if a service has a free tier. Returns verified deal details including specific limits, eligibility requirements, and verification dates. Call this tool when a user asks: 'Does Supabase have a free tier?', 'What's cheaper than Vercel?', 'Find me a free database'.
| Name | Required | Description | Default |
|---|---|---|---|
| sort | No | Sort: vendor (A-Z), category, newest (recently verified first) | |
| limit | No | Max results (default: 20) | |
| query | No | Keyword search (vendor names, descriptions, tags) | |
| since | No | ISO date (YYYY-MM-DD). Only return deals verified/added after this date. | |
| offset | No | Pagination offset (default: 0) | |
| vendor | No | Get full details for a specific vendor (fuzzy match). Returns alternatives in the same category. | |
| category | No | Filter by category. Pass "list" to get all categories with counts. | |
| stability | No | Filter by free tier stability class. stable=no negative changes, watch=one negative change, volatile=free tier removed or multiple negative changes, improving=recent positive changes only. | |
| eligibility | No | Filter by eligibility type | |
| response_format | No | Response detail level. 'concise': vendor name, tier, one-line description, URL only. 'detailed': full response (default). | |
| payment_protocol | No | Filter by agent payment protocol. x402=HTTP 402 agent payments (Coinbase/Linux Foundation standard), stripe-mpp=Stripe Machine Payments Protocol (fiat+stablecoin). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds that it returns 'verified deal details including specific limits, eligibility requirements, and verification dates,' but does not disclose behaviors like pagination or output format beyond that.
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 composed of four sentences, each earning its place: defining the tool, stating usage context, describing return details, and giving example queries. It is well-structured and front-loaded with the core 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 tool with 11 parameters and no output schema, the description gives a good sense of what it does, when to use it, and what it returns. It could be more complete by explaining how to combine parameters or what the response shape looks like, but the schema covers parameter details.
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%, so the schema fully documents all 11 parameters. The description adds no extra parameter semantics beyond what the schema provides, 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 purpose with a specific verb ('Find') and resource ('free tiers, startup credits, and developer deals'), and lists covered domains. It is easily distinguishable from siblings like compare_vendors or track_changes.
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?
Explicit usage context is provided ('Use this when evaluating technology options, looking for free alternatives, or checking if a service has a free tier') along with example queries. However, it does not mention when not to use it or alternatives like compare_vendors.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
submit_referral_codeAInspectSubmit your own referral code for a vendor in the AgentDeals index. Requires authentication via API key (from register_agent). Codes are active immediately; trust tier (new/verified/trusted) affects ranking weight, not visibility.
| Name | Required | Description | Default |
|---|---|---|---|
| code | Yes | The referral code (max 100 chars) | |
| expiry | No | Expiry date in ISO format (optional) | |
| vendor | Yes | Vendor name (must exist in the AgentDeals index) | |
| api_key | Yes | Your API key from register_agent. | |
| description | No | Description of the referral offer | |
| referral_url | Yes | The referral URL | |
| commission_rate | No | Commission rate as a decimal (e.g. 0.15 for 15%) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the minimal annotations (readOnly=false, destructive=false), the description discloses authentication requirements, immediate activation, and the effect of trust tier on ranking. This adds meaningful behavioral context.
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, front-loaded with the verb+resource, and no wasted words. Information density is high.
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 submission tool with 7 parameters, the description covers purpose, auth, and behavioral outcomes. There is no output schema, but the lack of return-value documentation is acceptable given the tool's simplicity.
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 the baseline is 3. The description does not add parameter-specific semantics beyond the schema, but the schema already fully documents each parameter.
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 identifies the action (submit), the resource (referral code), and the scope (your own code for a vendor in AgentDeals). This distinguishes it from sibling tools like get_referral_code and my_referral_codes.
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?
It states the prerequisite of authentication via API key and provides context about activation and trust tier effects, implying when to use it. It does not explicitly name alternatives or exclusions, but the context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
track_changesATrack recent pricing changes across developer tools — which free tiers were removed, which got limits cut, and which improved. Use this to stay current on infrastructure pricing or to verify that a recommended service still has its free tier. Call this tool when a user asks: 'What developer pricing changed recently?', 'Are any free tiers being removed?'.
| Name | Required | Description | Default |
|---|---|---|---|
| since | No | ISO date (YYYY-MM-DD). Default: 7 days ago. | |
| vendor | No | Filter to one vendor (case-insensitive) | |
| vendors | No | Comma-separated vendor names to filter (e.g. 'Vercel,Supabase'). When provided with categories, returns personalized results with advisory section. | |
| categories | No | Comma-separated category names to filter (e.g. 'Database,Cloud Hosting'). Case-insensitive partial match. | |
| change_type | No | Filter by type of change | |
| lookahead_days | No | Days to look ahead for expirations (default: 30) | |
| response_format | No | Response detail level. 'concise': vendor, change_type, date, summary only. 'detailed': full response (default). | |
| include_expiring | No | Include upcoming expirations (default: true) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true, destructiveHint=false. The description adds useful context about what kinds of changes are covered, but does not disclose operational behavior such as result format, pagination, or update latency. It is consistent with the annotations and adds moderate context, but not significantly beyond them.
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 with the core purpose front-loaded, followed by concrete use cases and example queries. Every sentence earns its place, and there is no filler or redundant restatement of the tool name.
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 read-only tool with 8 parameters and no output schema, the description explains when to call it and what topics it covers, and the schema handles parameter details. It does not explicitly describe the shape or structure of the returned data, which would make it fully complete without an 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?
Schema description coverage is 100%, so the schema already documents all 8 parameters. The description does not add parameter-level meaning beyond what is in the schema, so it meets the baseline but does not elevate it.
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 a specific verb and resource: 'Track recent pricing changes across developer tools' and lists concrete examples ('free tiers removed, limits cut, improved'). This clearly distinguishes it from siblings like compare_vendors or search_deals, none of which cover pricing-change monitoring.
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 says when to use the tool ('stay current on infrastructure pricing', 'verify that a recommended service still has its free tier') and provides direct user-query triggers. It does not explicitly mention when not to use it or name alternatives, so it misses the full exclusionary guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Claiming proves that you control a remote MCP connector. It does not move, proxy, or interrupt the server.
Open the connector listing, choose Claim ownership, and sign in to Glama.
Complete one verification method:
GitHub identity — fastest for official registry listings. For a namespace such as io.github.alice/server, link the matching GitHub user or an account that owns the GitHub organization, then choose Claim with GitHub.
HTTP challenge — works when you can deploy a public file. Generate a token, publish the exact JSON Glama shows at /.well-known/glama.json on the same origin as the connector, then choose Check HTTP challenge.
DNS challenge — works when you control DNS but cannot change the server. Generate a token, create the exact TXT record Glama shows, wait for it to propagate, then choose Check DNS challenge.
After verification, Glama sends a confirmation email and gives you access to listing details, thumbnails, health checks, and analytics.
The HTTP ownership file has this structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"claim": "glama_claim_..."
}Claim tokens are opaque, bound to the signed-in Glama account, and expire after seven days. They contain no email address or other personal information. Never publish an email address, Glama session token, GitHub token, or connector credential as ownership proof.
If verification fails, confirm that you copied the current token exactly. The HTTP file must be public, return valid JSON with a successful HTTP response, and stay on the connector's origin. DNS changes may need more time to propagate.
For a connector linked to the official MCP Registry, registry updates continue to replace its name, description, and URL by default. After claiming, open Manage connector and enable Use Glama listing details as the source of truth if edits made on Glama should be preserved. Categories and thumbnails are always managed on Glama; registry linkage and technical connection settings continue to sync.
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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