sourcesReturn available NewsAPI publisher sources, filterable by category, language, and country. Returns source id, name, description, URL, and category — use source ids to filter top_headlines or everything.
| Name | Required | Description | Default |
|---|---|---|---|
| country | No | ||
| category | No | ||
| language | No |
| Name | Required | Description | Default |
|---|---|---|---|
| status | No | API response status | |
| sources | No | Array of news source objects |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "category": "business",
+ "language": "en"
+ },
+ {
+ "country": "gb"
+ }
+]Output schema / (root)Previous value: -nullNew value: +{
+ "properties": {
+ "sources": {
+ "description": "Array of news source objects",
+ "items": {
+ "properties": {
+ "category": {
+ "description": "News category",
+ "type": "string"
+ },
+ "country": {
+ "description": "Country code",
+ "type": "string"
+ },
+ "description": {
+ "description": "Source description",
+ "type": "string"
+ },
+ "id": {
+ "description": "Source ID",
+ "type": "string"
+ },
+ "language": {
+ "description": "Language code",
+ "type": "string"
+ },
+ "name": {
+ "description": "Source name",
+ "type": "string"
+ },
+ "url": {
+ "description": "Source URL",
+ "type": "string"
+ }
+ },
+ "type": "object"
+ },
+ "type": "array"
+ },
+ "status": {
+ "description": "API response status",
+ "type": "string"
+ }
+ },
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, covering safety. The description adds domain-specific behavior: sources are filterable by category, language, and country, and returns specific fields (id, name, description, URL, category) 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?
Two sentences totaling 31 words, front-loaded with the action ('Return available NewsAPI publisher sources'). Every sentence earns its place, with no fluff or repetition of structured data.
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 has three optional parameters, no enums, and an output schema. The description covers purpose, filters, and downstream use, which is largely complete. It omits default behavior when no filters are applied, but given the simplicity and annotation richness, the description is adequate.
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 0% (parameters are just type 'string' with no descriptions), so the description must compensate. It names all three parameters and clarifies they act as filters, but does not provide valid values or format hints beyond what the schema examples show. This is partial compensation, not full.
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 available NewsAPI publisher sources, distinguishing it from siblings like top_headlines and everything by focusing on source metadata. The verb 'Return' and resource 'available NewsAPI publisher sources' are specific and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly advises using returned source ids to filter top_headlines or everything, providing a clear workflow and differentiating this tool from those siblings. It lacks explicit exclusionary language ('do not use for headlines'), but the context strongly implies the intended usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
There are several clusters of tools with overlapping purposes: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all route questions to data sources; entity_profile, compare_entities, and recent_changes all provide company research. The descriptions are detailed, but an agent could easily misselect among these near-duplicates, especially since ask_pipeworx_beta is explicitly identical to ask_pipeworx right now.
Placeholder for naming consistency placeholder
34 tools for a server named Newsapi is an extreme scope mismatch. Only three tools (everything, top_headlines, sources) are news-related; the rest cover data research, prediction markets, memory, subscriptions, and package scanning, which belongs in separate servers. The count is also past the 25+ range that feels overloaded for any single purpose.
The three NewsAPI tools themselves cover the standard news surface (top_headlines, everything, sources) with no major gaps. However, the server's stated purpose is diluted by ~30 unrelated tools, and the non-news tools form an incoherent assortment with no clear unified domain to assess completeness against. The mismatch makes completeness hard to reason about and degrades the overall usefulness.