RentSeek Evidence
Server Details
Source-linked executive compensation data for AI agents and developers.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
Available Tools
5 toolsget_claim_evidenceGet Claim EvidenceARead-onlyInspect
Returns the value, filing source, release identity, methodology version, and current or superseded status for a RentSeek clm_... claim ID. Requires OAuth or X-API-KEY and costs 1 credit. The result is filing evidence, not investment advice.
| Name | Required | Description | Default |
|---|---|---|---|
| claim_id | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true, so the description adds value by disclosing the credit cost and a disclaimer ('not investment advice'). No contradictions, and the extra context about auth requirements further aids an agent in understanding behavioral constraints beyond safety.
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: first clearly states what the tool returns, second adds essential context (auth, cost, disclaimer). No unnecessary words, but could be more structured with bullet points or clearer separation of concerns.
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 lists five returned fields but does not specify their format or structure (no output schema). Given the tool's simplicity (one param), this is moderate but not fully complete – an agent might need to infer the response shape. For a tool without output schema, more detail on the output structure would improve completeness.
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 0% description coverage; the description compensates minimally by noting that the claim ID is a RentSeek `clm_...` ID, adding format context. However, it does not elaborate on the parameter's purpose or constraints beyond the schema's minLength, leaving significant gap for the agent.
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 the tool returns specific fields (value, filing source, etc.) for a RentSeek claim ID, using a specific verb 'Returns'. The resource is well-defined as 'claim evidence' and is distinct from sibling tools like get_company_dossier or list_available_tickers.
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 required authentication (OAuth or X-API-KEY) and cost (1 credit), which provides context but does not explicitly guide when to use this tool vs alternatives. Implicitly, it is for retrieving claim evidence by ID, but no when-not-to-use or sibling comparisons.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_company_dossierGet Company Evidence DossierARead-onlyInspect
Returns a sourced company dossier for a ticker, including executives, compensation history, pay ratio, pay-versus-performance, claims, and release provenance, with optional full or compact format and field projection. Requires OAuth or X-API-KEY and costs 3 credits. The result is filing evidence, not investment advice.
| Name | Required | Description | Default |
|---|---|---|---|
| fields | No | ||
| format | No | full | |
| ticker | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true. Description adds that it costs 3 credits, requires OAuth or X-API-KEY, and that results are filing evidence not investment advice. 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 sentences, front-loaded with purpose, no fluff. Every sentence adds essential 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?
No output schema, but description lists key contents and qualifies the result as filing evidence. Could elaborate on return structure or pagination, but it's reasonably complete for a dossier retrieval tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so description must compensate. It mentions 'ticker' (implied), 'optional full or compact format', and 'field projection'. It lists some fields (e.g., executives, compensation_history) but does not fully enumerate all enum values from the schema (e.g., company, sources, limitations are missing). Adds partial meaning.
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 the tool returns a sourced company dossier for a ticker, listing specific contents like executives, compensation, pay ratio, etc. Distinguishes from sibling tools like get_executive_compensation (narrower) or get_claim_evidence (specific to claims).
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?
Specifies authentication requirements and credit cost, but does not explicitly state when to use this tool vs siblings or when not to use it. Lacks explicit alternatives or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_executive_compensationGet Executive CompensationARead-onlyInspect
Returns annual named-executive compensation rows for a company identified by ticker or CIK, with fiscal-year filters, pay components, totals, and filing source URLs. Latest-FY requests cost 0 credits; historical, range, or multi-FY requests require OAuth or X-API-KEY and cost 1 credit. Pay ratio, pay-versus-performance, and company dossiers are not included. The result is filing data, not investment advice.
| Name | Required | Description | Default |
|---|---|---|---|
| cik | No | ||
| limit | No | Maximum fiscal years to return. Defaults to the latest year only. | |
| period | No | annual | |
| ticker | No | ||
| fiscal_year | No | Exact fiscal year. Omit all fiscal-year filters to get the latest year. | |
| fiscal_year_gte | No | Inclusive earliest fiscal year. Omit all fiscal-year filters to get the latest year. | |
| fiscal_year_lte | No | Inclusive latest fiscal year. Omit all fiscal-year filters to get the latest year. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses credit cost differences based on filters, authentication requirements, and that the result is filing data, not investment advice. The readOnlyHint annotation is consistent with the read nature; description adds value beyond annotations by explaining costs and disclaimers.
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 for the amount of information conveyed. It front-loads the core purpose and then adds usage details. Every sentence adds value, though could be slightly trimmed without losing meaning.
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, the description mentions pay components, totals, and filing source URLs, giving a reasonable idea of the response. However, it does not specify the exact structure or field names, which would be helpful for a tool with 7 parameters and no 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 coverage is 57% (4/7 params described). The description adds context about parameter combinations (e.g., 'Omit all fiscal-year filters to get the latest year'), which helps, but does not detail individual params beyond what schema provides. At moderate coverage, description partially compensates but not fully.
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 named-executive compensation rows for a company by ticker/CIK with fiscal-year filters and pay components. It explicitly excludes pay ratio, pay-versus-performance, and dossiers, distinguishing it from sibling tools like get_company_dossier.
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 specific guidance on when to use: latest-FY requests cost 0 credits and no auth, while historical/range/multi-FY require OAuth/X-API-KEY and cost 1 credit. It notes exclusions (pay ratio, etc.), but does not directly compare to siblings for when to choose this over alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_available_tickersList Available TickersARead-onlyInspect
Returns ticker symbols for companies with published RentSeek executive-compensation data. No authentication is required, and the request costs 0 credits. The result contains availability only, not compensation values. It is not investment advice.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations (readOnlyHint=true, openWorldHint=false), the description clarifies that the result contains only availability, not compensation values, and adds a disclaimer that it is not investment advice. This provides useful context without contradicting 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?
Three sentences: purpose, cost/auth context, and scope disclaimer. All earn their place, no redundant text. Front-loaded with the core function.
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 and 0 parameters, the description adequately explains the returned data (tickers) and its limitation (no compensation values). It could mention ordering or if the list is exhaustive, but the current version is mostly complete for a simple listing tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters and schema description coverage is 100% (trivially). The description does not need to add parameter meaning; its mention of 'no authentication' is behavioral, not parameter-related. Baseline 4 for 0 parameters is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns ticker symbols for companies with published RentSeek executive-compensation data. It uses a specific verb ('Returns') and a well-defined resource, distinguishing it from sibling tools like get_company_dossier or get_executive_compensation.
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 notes that no authentication is required and costs 0 credits, implying low friction for use, but does not explicitly specify when to use this tool versus alternatives (e.g., for initial ticker discovery before fetching compensation). No exclusions or when-not-to-use guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_material_changesList Material Compensation ChangesARead-onlyInspect
Returns classified executive-compensation disclosure changes for 1-50 tickers since an inclusive date or timestamp, with configurable thresholds and cursor pagination. Requires OAuth or X-API-KEY and costs 2 credits per page. Current compensation snapshots and full historical rows are not included. The result is filing evidence, not investment advice.
| Name | Required | Description | Default |
|---|---|---|---|
| since | Yes | Inclusive ISO date or timestamp from the caller's prior feed run. | |
| cursor | No | Opaque next_cursor from a prior response. Omit for the first page. | |
| tickers | Yes | Ticker symbols to monitor. Pass 1-50 symbols in one request. | |
| page_size | No | Events per page. Omit to use 25; maximum 100. | |
| classification | No | Event classification to return. Omit to return material events only; use all to include informational events. | material |
| threshold_total_pct | No | Material total-compensation change percent. Omit to use 20%. | |
| threshold_component_pct | No | Material compensation-component change percent. Omit to use 30%. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds behavioral context beyond the readOnlyHint and openWorldHint annotations: it requires OAuth or X-API-KEY, costs 2 credits per page, and notes the result is filing evidence, not investment advice. 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 four sentences long and front-loads the main purpose. Most sentences are informative, though the disclaimer about investment advice is marginally necessary. Overall 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 no output schema, the description does not detail the structure of returned events (e.g., fields included). It mentions pagination and classification but omits the exact response format. For a tool with 7 parameters, more completeness on output would be helpful.
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 100% schema description coverage, the baseline is 3. The description adds value by explaining concepts like 'inclusive date or timestamp', 'opaque next_cursor', and the 1-50 ticker limit, enhancing clarity beyond the schema alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns classified executive-compensation disclosure changes for 1-50 tickers since an inclusive date. It specifies what is included (changes, not snapshots or full history) and distinguishes from sibling tools by focusing on material 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?
The description mentions authentication requirements (OAuth or X-API-KEY) and cost (2 credits per page). It also states it does not include current snapshots or full historical rows, providing some guidance when not to use it. However, it does not explicitly compare to sibling tools like get_executive_compensation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Frequently Asked Questions
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.jsonon 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. Keep the HTTP file or DNS record in place: Glama periodically checks it and ownership remains verified while the token is discoverable.
The HTTP ownership file has this structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"claim": "glama_claim_..."
}Claim tokens are opaque, stable, and bound to the signed-in Glama account. They contain no email address or other personal information. If Glama can no longer discover a verified HTTP or DNS token, it starts a seven-day grace period before removing claim-based access. Restore the same token during that period to keep ownership verified. 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. A claim cannot transfer to a different origin or hostname: if the connector target changes, Glama starts the grace period and the new target must be claimed separately after the previous claim is released.
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.
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Keep tool definitions clear and complete to earn a high Tool Definition Quality Score (TDQS)
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Discussions
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TDQS
Each tool targets a distinct aspect of executive compensation data: claim evidence, full company dossier, compensation rows, ticker listing, and material changes. Descriptions clearly differentiate them, preventing confusion.
All tools follow a consistent verb_noun pattern using snake_case: get_* for retrieval and list_* for enumeration. No mixing of styles or irregular verbs.
Five tools is well-scoped for the domain of accessing executive compensation filing data. Each tool provides essential functionality without unnecessary bloat or gaps.
The tool set covers core operations: retrieving evidence, dossiers, compensation details, available tickers, and material changes. A minor gap is the lack of a direct tool for bulk compensation data across multiple companies, but the set is largely complete.