Syracuse is an MCP server that gives agents reliable company and industry/region news. Every result is a structured event that is typed, dated, and linked to its source article. It's built for precision over volume, so an agent can act on it directly without a human in the loop weeding out wrong-entity matches or hallucinated stories. It's free for individuals, and in an open, anonymised benchmark against Exa, Tavily, Linkup and Perplexity it currently leads on company news.
Location Groups are a way of grouping GeoNamesLocation entities into a simplified hierarchy.
They start from top-level regions using the United Nations M49 standard (Region/Sub-Region/Intermediate Region). The US is further broken down United States Census Bureau regions (e.g. East/West etc) and then into individual states. Certain other countries are also broken down into their states/provinces: AE, CA, CN, IN.
| Name | Required | Description | Default |
|---|---|---|---|
| page | No | A page number within the paginated result set. | |
| page_size | No | Number of results to return per page. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the full burden of behavioral disclosure. It fails to mention what the tool returns (e.g., a paginated list), pagination behavior, or that it is a read-only operation. The description only explains the data model, not the tool's behavior.
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 (three sentences) and well-structured, front-loading the definition of Location Groups. Every sentence adds context about the hierarchy, though the tool's actual operation is left implicit. No waste, but could be tighter.
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?
This is a simple list tool with only two optional parameters and no output schema. The description provides rich domain context but omits what the response looks like and any direct statement of return type. For a tool to be correctly invoked, an agent needs to know it returns a list and how pagination works; this description doesn't cover that.
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 100% description coverage for both parameters (page and page_size), so the schema already explains them fully. The description adds no parameter-specific meaning. According to the baseline rule for high schema coverage, a 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 tool name 'location_groups_list' clearly indicates a list operation, but the description never explicitly states 'lists location groups' or 'returns location groups'. Instead it provides background on what Location Groups are, which is helpful but leaves the actual function implied. This is clear from the name but not from the description, so it's a moderate purpose 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 gives no guidance on when to use this tool versus alternatives. It implies usage when you need location groups, but doesn't state any selection criteria, exclusions, or mention any alternative. Sibling tools are different domains, so no differentiation is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Creates a user account with the given email, sends a verification email, and returns an API token. Unverified users are limited to 30 queries/month; verified users can make 300/month for free. Drop us an email to tell us how you found the service and if you want more queries (see website footer)
| Name | Required | Description | Default |
|---|---|---|---|
| Yes | User email address |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of disclosing behavior. It transparently reveals that the tool creates an account, sends a verification email, returns a token, and imposes rate limits (30/month unverified, 300/month verified). It also mentions how to request more queries, which adds useful context beyond the bare action.
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, front-loaded with the main purpose. The second sentence adds important limitations and a user note. There is no redundant information or unnecessary length.
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?
This is a single-parameter tool with no annotations and no output schema. The description explains the full flow (account creation, verification email, token return, rate limits) and is sufficient for an agent to understand the behavior. The sibling tools are all list operations, so this tool's purpose is unambiguous.
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 covers 100% of the parameter descriptions with a 'User email address' and the format 'email'. The description merely references 'the given email' without adding additional meaning or constraints beyond what the schema already provides. Thus, baseline 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 verb 'creates' with the resource 'user account', and also mentions sending a verification email and returning an API token. This specific behavior distinguishes it from the sibling list tools, which are all about querying data.
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 about when to use this tool (for registration and obtaining an API key) but does not explicitly mention alternatives or exclusions. The sibling tools are clearly different, so the usage context is sufficient without needing explicit 'when not to use' guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Stories by Industry/Location Simplified endpoint that runs the same logic as the main stories endpoint, with a restricted parameter set (industry and the location the story happened in). Stories can either be
-- IndustrySectorUpdate
or activities in an organization's lifecycle. We track the following activities:
-- CorporateFinanceActivity: M&A, investments, stock purchases
-- PartnershipActivity: Partnership between 2 or more organizations. Often, companies describe their customers as their partners. This type of activity covers both genuine partnerships and customer/supplier relationships
-- RoleActivity: Key change in senior personnel, e.g. replacing CEO
-- LocationActivity: Opening or closing a new location (e.g. setting up in EMEA or shutting down a factory in a particular town)
-- ProductActivity: New product launches
-- AnalystRatingActivity: Updates from industry analysts
-- EquityActionsActivity: Stock repurchases, dividends etc
-- FinancialReportingActivity: Notice that an organization is going to announce its financials
-- FinancialsActivity: Information about company financials, e.g. revenue or EBITDA
-- IncidentActivity: Adverse incidents e.g. safety
-- LegalActivity: Lawsuits or activities that could lead to lawsuits, e.g. SEC investigations
-- MarketingActivity: e.g. launching a new advertising campaign
-- OperationsActivity: Company operations news, e.g. we are investing in a new product, or we have just completed an security audit
-- RecognitionActivity: e.g. we are delighted to announce that we won Agency of the Year
-- RegulatoryActivity: Legal or regulatory activity affecting this organizationg e.g. permit for drilling, or regulatory filing
Parameters:
activity_location: Location group name or id (e.g. "texas", "india", "MidWest", "FR", "us-ca") where the story happened. Not case sensitive. Accepts multiple values. They must each match an id or name from the location groups endpoint.
activity_location_id: Location group identifiers (e.g., "Southern Asia", "BT", "US-CA") where the story happened. Case-sensitive. Accepts multiple values. They must each match an id from the location groups endpoint.
include_provenance: Add a source_audit field to each story explaining how it was surfaced (source path, Typesense match score, and the entity that carried it). Defaults to false.
industry: Industry name to filter by. Accepts multiple values.
industry_context: Optional context aspects to anchor the industry search in. Pass each aspect as a separate value. Can be a broader category name or detailed examples (e.g. "Movie Industry" when searching for "Distribution", or "BOPP Film" and "BOPET Film" when searching for "Film"). Applied to every value of industry in the same request.
industry_id: Industry ID (topic ID) to filter by. Accepts multiple values. They must each match a topic_id from the industry-clusters endpoint.
location: Deprecated alias of activity_location, kept for backwards compatibility. It means the location the story happened in, not where the company is based.
location_id: Deprecated alias of activity_location_id, kept for backwards compatibility. It means the location the story happened in, not where the company is based.
output: Output format. Defaults to "simple" (SimpleStory schema). Use "full" for the detailed response.
page: A page number within the paginated result set.
page_size: Number of results to return per page.
| Name | Required | Description | Default |
|---|---|---|---|
| page | No | A page number within the paginated result set. | |
| output | No | Output format. Defaults to "simple" (SimpleStory schema). Use "full" for the detailed response. | |
| industry | No | Industry name to filter by. Accepts multiple values. | |
| location | No | Deprecated alias of `activity_location`, kept for backwards compatibility. It means the location the story happened in, not where the company is based. | |
| page_size | No | Number of results to return per page. | |
| industry_id | No | Industry ID (topic ID) to filter by. Accepts multiple values. They must each match a topic_id from the [industry-clusters](#/industry-clusters/industry-clusters_list) endpoint. | |
| location_id | No | Deprecated alias of `activity_location_id`, kept for backwards compatibility. It means the location the story happened in, not where the company is based. | |
| industry_context | No | Optional context aspects to anchor the industry search in. Pass each aspect as a separate value. Can be a broader category name or detailed examples (e.g. "Movie Industry" when searching for "Distribution", or "BOPP Film" and "BOPET Film" when searching for "Film"). Applied to every value of `industry` in the same request. | |
| activity_location | No | Location group name or id (e.g. "texas", "india", "MidWest", "FR", "us-ca") where the story happened. Not case sensitive. Accepts multiple values. They must each match an id or name from the [location groups](#/location-groups/location-groups_list) endpoint. | |
| include_provenance | No | Add a `source_audit` field to each story explaining how it was surfaced (source path, Typesense match score, and the entity that carried it). Defaults to false. | |
| activity_location_id | No | Location group identifiers (e.g., "Southern Asia", "BT", "US-CA") where the story happened. Case-sensitive. Accepts multiple values. They must each match an id from the [location groups](#/location-groups/location-groups_list) endpoint. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the disclosure burden. It usefully discloses parameter behavior (case sensitivity, deprecated aliases, provenance flag, output modes) but does not describe pagination defaults, rate limits, or return payload shape; because it is a list endpoint, mutation risk is implicitly low but not stated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded and uses clear headings, but it is long and duplicates the schema's parameter documentation, plus a 14-item activity taxonomy that dilutes focus. Structured, but not tight; the activity-type list could be trimmed without losing tool-invocation 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?
With 11 optional parameters, no annotations, and no output schema, the description covers all parameters and key behavior (deprecated aliases, provenance, output mode). It lacks pagination defaults and a full return-value description, but is substantially complete for a filtering endpoint.
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 covers all 11 parameters, so the baseline is 3; the description's parameter section reinforces and expands with examples ('texas', 'MidWest', 'FR'), case-sensitivity caveats, deprecation aliases, and cross-links to reference endpoints. However, most of this text duplicates the schema descriptions, so it earns only modest extra credit.
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 identifies this as a simplified stories endpoint scoped to industry and location, and enumerates the story/activity types returned. It does not explicitly contrast it with the sibling stories_organization_list, so sibling differentiation is only implicit.
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 says this is a simplified endpoint with a restricted parameter set (industry and location), implying when it applies. It does not explicitly state when to use this over stories_organization_list or the main stories endpoint, nor provide exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Stories by Organization
Simplified endpoint that runs the same logic as the main stories endpoint, with a restricted parameter set: org_name, optionally narrowed by where the company is based (org_location), what it does (industry), and where its stories happened (activity_location). Stories can either be
-- IndustrySectorUpdate
or activities in an organization's lifecycle. We track the following activities:
-- CorporateFinanceActivity: M&A, investments, stock purchases
-- PartnershipActivity: Partnership between 2 or more organizations. Often, companies describe their customers as their partners. This type of activity covers both genuine partnerships and customer/supplier relationships
-- RoleActivity: Key change in senior personnel, e.g. replacing CEO
-- LocationActivity: Opening or closing a new location (e.g. setting up in EMEA or shutting down a factory in a particular town)
-- ProductActivity: New product launches
-- AnalystRatingActivity: Updates from industry analysts
-- EquityActionsActivity: Stock repurchases, dividends etc
-- FinancialReportingActivity: Notice that an organization is going to announce its financials
-- FinancialsActivity: Information about company financials, e.g. revenue or EBITDA
-- IncidentActivity: Adverse incidents e.g. safety
-- LegalActivity: Lawsuits or activities that could lead to lawsuits, e.g. SEC investigations
-- MarketingActivity: e.g. launching a new advertising campaign
-- OperationsActivity: Company operations news, e.g. we are investing in a new product, or we have just completed an security audit
-- RecognitionActivity: e.g. we are delighted to announce that we won Agency of the Year
-- RegulatoryActivity: Legal or regulatory activity affecting this organizationg e.g. permit for drilling, or regulatory filing
Parameters:
activity_location: Location group name or id (e.g. "texas", "india", "MidWest", "FR", "us-ca") where the story happened. Not case sensitive. Accepts multiple values. They must each match an id or name from the location groups endpoint.
activity_location_id: Location group identifiers (e.g., "Southern Asia", "BT", "US-CA") where the story happened. Case-sensitive. Accepts multiple values. They must each match an id from the location groups endpoint.
industry: Industry name the company must work in. Narrows which companies match org_name. Accepts multiple values.
industry_context: Optional context aspects to anchor the industry search in. Pass each aspect as a separate value. Can be a broader category name or detailed examples (e.g. "Movie Industry" when searching for "Distribution", or "BOPP Film" and "BOPET Film" when searching for "Film"). Applied to every value of industry in the same request.
industry_id: Industry ID (topic ID) the company must belong to. Narrows which companies match org_name. They must each match a topic_id from the industry-clusters endpoint.
location: Deprecated alias of activity_location, kept for backwards compatibility. It means the location the story happened in, not where the company is based.
location_id: Deprecated alias of activity_location_id, kept for backwards compatibility. It means the location the story happened in, not where the company is based.
org_location: Location group name or id where the company is based. Narrows which companies match org_name, so it may only be used together with org_name. Not case sensitive. Accepts multiple values. For stories that happened in a place use activity_location instead.
org_location_id: Location group identifiers (e.g., "Southern Asia", "BT", "US-CA") where the company is based. Case-sensitive. May only be used together with org_name.
org_name: Filter by organization name (partial match). (required)
output: Output format. Defaults to "simple" (SimpleStory schema). Use "full" for the detailed response.
page: A page number within the paginated result set.
page_size: Number of results to return per page.
| Name | Required | Description | Default |
|---|---|---|---|
| page | No | A page number within the paginated result set. | |
| output | No | Output format. Defaults to "simple" (SimpleStory schema). Use "full" for the detailed response. | |
| industry | No | Industry name the company must work in. Narrows which companies match `org_name`. Accepts multiple values. | |
| location | No | Deprecated alias of `activity_location`, kept for backwards compatibility. It means the location the story happened in, not where the company is based. | |
| org_name | Yes | Filter by organization name (partial match). | |
| page_size | No | Number of results to return per page. | |
| industry_id | No | Industry ID (topic ID) the company must belong to. Narrows which companies match `org_name`. They must each match a topic_id from the [industry-clusters](#/industry-clusters/industry-clusters_list) endpoint. | |
| location_id | No | Deprecated alias of `activity_location_id`, kept for backwards compatibility. It means the location the story happened in, not where the company is based. | |
| org_location | No | Location group name or id where the company is *based*. Narrows which companies match `org_name`, so it may only be used together with `org_name`. Not case sensitive. Accepts multiple values. For stories that happened in a place use `activity_location` instead. | |
| org_location_id | No | Location group identifiers (e.g., "Southern Asia", "BT", "US-CA") where the company is *based*. Case-sensitive. May only be used together with `org_name`. | |
| industry_context | No | Optional context aspects to anchor the industry search in. Pass each aspect as a separate value. Can be a broader category name or detailed examples (e.g. "Movie Industry" when searching for "Distribution", or "BOPP Film" and "BOPET Film" when searching for "Film"). Applied to every value of `industry` in the same request. | |
| activity_location | No | Location group name or id (e.g. "texas", "india", "MidWest", "FR", "us-ca") where the story happened. Not case sensitive. Accepts multiple values. They must each match an id or name from the [location groups](#/location-groups/location-groups_list) endpoint. | |
| activity_location_id | No | Location group identifiers (e.g., "Southern Asia", "BT", "US-CA") where the story happened. Case-sensitive. Accepts multiple values. They must each match an id from the [location groups](#/location-groups/location-groups_list) endpoint. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavior. It does add meaningful context by enumerating 15 activity types (e.g., 'CorporateFinanceActivity,' 'IncidentActivity') that define what stories are included, and it clarifies deprecated aliases. However, it does not mention whether the operation requires authentication, has rate limits, or if it is read-only (though 'list' implies read). It also doesn't describe error scenarios or pagination behavior beyond the parameters. For a list endpoint with no annotations, this is adequate but not exhaustive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a summary, an extensive list of activity types, and parameter explanations. However, the long enumeration of 15 activity types is verbose and could be condensed without losing critical invocation details. The front-loaded summary is good, but the activity list adds bulk that may dilute focus. It's not overly long for the complexity, but it could be more concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 13 parameters, no output schema, and no annotations, the description covers a lot: the relationship between parameters, constraints (e.g., 'org_location' may only be used with 'org_name'), and references to other endpoints for valid values. It explains the 'output' parameter and pagination. While it doesn't describe the response structure (no output schema exists), it gives enough context for an agent to invoke the tool correctly. It is reasonably complete for a list endpoint.
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 description adds value beyond the schema by providing examples (e.g., 'texas', 'india' for activity_location), clarifying case sensitivity, and explaining the difference between 'org_location' and 'activity_location.' It also cross-references other endpoints (location_groups, industry-clusters) and explains deprecated aliases. This goes well beyond the schema's bare 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's purpose: 'Stories by Organization' and labels it a 'Simplified endpoint that runs the same logic as the main stories endpoint, with a restricted parameter set.' This goes beyond a tautology and clarifies the resource (stories) and filter (organization). However, it doesn't explicitly distinguish it from the sibling tool 'stories_industry_location_list' beyond mentioning 'main stories endpoint,' so it loses a point for not naming direct alternatives.
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 context by saying it's a 'simplified endpoint' with a restricted parameter set, but it does not explicitly state when to use this tool versus the main stories endpoint or the sibling 'stories_industry_location_list.' It also doesn't mention when not to use it. The context is clear (filter stories by organization) but lacks explicit alternative 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. 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.
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
To improve your MCP server's ranking:
Claim ownership of the server listing
Complete the server profile with an accurate description and thumbnail
Provide a test profile so Glama can connect to and evaluate the server
Keep tool definitions clear and complete to earn a high Tool Definition Quality Score (TDQS)
Route real usage through the Glama Gateway; more recorded successful server uses also improve the ranking
For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
Centralized credential management – store and rotate API keys and OAuth tokens in one place
Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
The server is experiencing an outage
The URL of the server is wrong
Credentials required to access the server are missing or invalid
If you are the owner of this MCP connector and would like to make modifications to the listing, including providing test credentials for accessing the server, please contact support@glama.ai.
No comments yet. Be the first to start the discussion!
Add one secure layer between your agents and this server.
Each tool has a clearly distinct purpose: location_groups_list provides reference data for location groups, register_and_get_key_create handles user authentication, and the two stories endpoints filter by different primary criteria (industry/location vs organization). The descriptions and required parameters make it easy to choose the right tool.
Tool names follow no consistent pattern. Two end with '_list' but one is a multi-action verb phrase ('register_and_get_key_create'), and the stories endpoints mix descriptor order. This inconsistent naming could confuse agents trying to predict similar tool names.
Four tools is a well-scoped size for a focused news API, covering authentication, location reference, and two primary story query paths. It avoids bloat while providing essential functionality.
The server covers story retrieval by industry/location and organization, but lacks a general story listing, an industry enumeration endpoint, or a way to fetch a single story by ID. These gaps may require agents to use workarounds or incomplete data.