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.
Glama MCP Gateway
Connect through Glama MCP Gateway for full control over tool access and complete visibility into every call.
Full call logging
Every tool call is logged with complete inputs and outputs, so you can debug issues and audit what your agents are doing.
Tool access control
Enable or disable individual tools per connector, so you decide what your agents can and cannot do.
Managed credentials
Glama handles OAuth flows, token storage, and automatic rotation, so credentials never expire on your clients.
Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Average 3.5/5 across 4 of 4 tools scored. Lowest: 2.6/5.
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.
location_groups_listCInspectLocation 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.
register_and_get_key_createAInspectCreates 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_industry_location_listAInspectStories by Industry/Location Simplified endpoint that runs the same logic as the main stories endpoint, with a restricted parameter set (only industry and 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:
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 (e.g. "Packaging" when searching for "Rigid Metal"). Applied to every value of industry in the same request.
location: Location group name or id (e.g. "texas", "india", "MidWest", "FR", "us-ca"). Not case sensitive. Accepts multiple values. They must each match an id or name from the location groups endpoint.
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 | Location group name or id (e.g. "texas", "india", "MidWest", "FR", "us-ca"). Not case sensitive. Accepts multiple values. They must each match an id or name from the [location groups](#/location-groups/location-groups_list) endpoint. | |
| page_size | No | Number of results to return per page. | |
| industry_context | No | Optional context aspects to anchor the industry search in. Pass each aspect as a separate value (e.g. "Packaging" when searching for "Rigid Metal"). Applied to every value of `industry` in the same request. | |
| 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. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. It extensively enumerates the activity types returned (e.g., CorporateFinanceActivity, ProductActivity), giving a clear sense of what stories will appear. It also explains the `include_provenance` behavior. However, it doesn't state whether the operation is read-only or any auth requirements, though that is typical for list endpoints.
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 longer than necessary; the parameter section duplicates the schema word-for-word. The activity type list is informative but adds bulk. The opening sentence is succinct and the structure is clear, but the redundancy reduces conciseness.
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 explains the story taxonomy well, which is essential for understanding results, but it lacks a description of the response schema or pagination behavior. It references 'SimpleStory schema' without elaborating, and no output schema is provided. For a list endpoint with many parameters, this is a notable 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?
The input schema already provides detailed descriptions for all 7 parameters with 100% coverage. The description repeats the parameter list exactly, adding no additional semantics beyond what the schema offers. For example, 'Accept multiple values' is already in the 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 the endpoint is a 'Simplified endpoint that runs the same logic as the main stories endpoint' with a restricted parameter set, explicitly distinguishing it from the broader stories endpoint. The name and description together specify it lists stories by industry/location.
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 when only industry/location filters are needed, calling it a 'Simplified endpoint' with a 'restricted parameter set'. It does not explicitly name alternatives (e.g., the main stories endpoint) or provide when-not-to-use guidance, so usage is implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
stories_organization_listBInspectStories by Organization Simplified endpoint that runs the same logic as the main stories endpoint, with a restricted parameter set (only org_name). 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:
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. | |
| org_name | Yes | Filter by organization name (partial match). | |
| page_size | No | Number of results to return per page. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must carry the full burden. It explains the behavioral scope of the endpoint (same logic as main endpoint, restricted to org_name) and enumerates the types of activities that can appear, which is valuable context. However, it does not explicitly disclose the read-only nature, auth requirements, or pagination behavior, leaving some gaps for a tool with no annotation safety signals.
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 excessively long, with a verbose list of 11 activity types, each with multi-line explanations. While the purpose is front-loaded, the parameter section duplicates the schema and the activity type list could be summarized. Many sentences do not earn their place, making the description unwieldy for an AI agent to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description provides rich domain context about the types of stories returned, which helps an agent understand the semantics of the data. However, it lacks explicit information about return value structure (though there is no output schema), pagination behavior beyond the parameters, and error handling. The explanation of activity types partially compensates for the missing output schema, but the overall completeness is only moderate.
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 repeats the parameter descriptions exactly from the schema (org_name, output, page, page_size), adding no extra semantic value beyond what the schema already provides. It does mention 'restricted parameter set (only org_name)' but this is already evident from the 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 that this endpoint returns stories by organization and is a simplified version of the main stories endpoint with a restricted parameter set. It identifies the resource (stories) and the scope (organization), and differentiates itself from the main stories endpoint. However, it lacks an explicit verb like 'list' or 'get', and does not directly distinguish itself from the sibling tool 'stories_industry_location_list'.
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: it is a simplified endpoint with only org_name as a filter, implying it should be used when you need stories for a specific organization and don't need additional filters from the main endpoint. It does not explicitly state alternatives or when not to use it beyond the restriction to org_name, so it misses the full 'when-not' guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Claim this connector by publishing a /.well-known/glama.json file on your server's domain with the following structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
}The email address must match the email associated with your Glama account. Once published, Glama will automatically detect and verify the file within a few minutes.
Control your server's listing on Glama, including description and metadata
Access analytics and receive server usage reports
Get monitoring and health status updates for your server
Feature your server to boost visibility and reach more users
For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
Centralized credential management – store and rotate API keys and OAuth tokens in one place
Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
The server is experiencing an outage
The URL of the server is wrong
Credentials required to access the server are missing or invalid
If you are the owner of this MCP connector and would like to make modifications to the listing, including providing test credentials for accessing the server, please contact support@glama.ai.
No comments yet. Be the first to start the discussion!
