GDELT Global Events
Server Details
Geopolitical event detection, tone timeseries, actor trends from GDELT 2.0.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- guptaprakhariitr/gdelt-events-mcp
- GitHub Stars
- 1
- Server Listing
- gdelt-events-mcp
TDQS
Each tool targets a distinct function: event search, tone timeseries, and trending actors. There is no overlap in purpose.
All tools follow the pattern 'gdelt_<noun>_<plural_noun>' with descriptive names using underscores. Naming is fully consistent.
Three tools are appropriate for a focused global events MCP server, covering core capabilities without bloat.
The tools cover search, tone analysis, and actor trends. Missing date-range filtering for search and detailed event lookup are minor gaps for a basic events server.
Available Tools
3 toolsgdelt_search_eventsBInspect
Search global news for events matching a query. Optionally filter by source country (ISO 2-letter) or domain. Returns recent articles with title, URL, source, language, country, tone.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | GDELT search query, supports operators like quotes and OR. | |
| domain | No | Filter to one publishing domain. | |
| country | No | Source-country filter (ISO 2-letter, e.g. 'IN', 'US'). | |
| timespan | No | e.g. '1d', '7d', '1m'. Default '1d'. | 1d |
| max_records | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. It states it returns recent articles with specific fields, but lacks details about ordering, pagination, rate limits, or how recency is defined. This leaves important behavioral aspects undisclosed.
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, consisting of two sentences. The first sentence states the primary purpose, and the second lists optional filters and return fields. Every sentence contributes useful information without 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 tool with 5 parameters and no output schema, the description covers the core functionality: what it searches, optional filters, and the return fields. It lacks details on result ordering and error handling, but the provided information is sufficient for basic usage.
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 high (80%), so the baseline is 3. The description reiterates the optional country and domain filters but does not add significant meaning beyond the schema. It does not clarify the query operators or timespan format beyond what the schema already provides.
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 searches global news events with a query and optional filters. It is specific about the resource and verb. However, it does not explicitly differentiate from sibling tools (tone timeseries and trending actors), which slightly reduces 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 implies usage context by mentioning optional filters and return fields, but it provides no explicit guidance on when to use this tool versus alternatives, nor any exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
gdelt_tone_timeseriesCInspect
Sentiment-tone timeseries for a query. Returns one row per time step (hourly or daily) with the average tone (-10 most negative, +10 most positive) and article volume.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | ||
| country | No | ||
| timespan | No | 7d | |
| granularity | No | day |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description discloses tone range and output granularity, but omits potential side effects, authentication needs, or error handling. For a read-only analytics tool, it is adequate but not detailed.
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?
Single sentence, front-loaded with purpose, and no unnecessary words. It efficiently conveys the core idea.
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 4 parameters and no output schema, the description leaves gaps: no description of country, timespan, or query format. Output is partially described but not complete (e.g., pagination, date range).
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%, so description must compensate. It only clarifies granularity ('hourly or daily') and implies query usage. Does not explain country, timespan format, or query syntax.
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 a sentiment-tone timeseries for a query, with average tone and volume per time step. It implicitly distinguishes from siblings by specifying aggregated temporal output, but lacks explicit comparison.
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?
No guidance on when to use this tool vs. siblings (gdelt_search_events, gdelt_trending_actors). The description does not mention use cases or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
gdelt_trending_actorsBInspect
Top mentioned named entities (people, organizations, places) in news for a country in the last N hours. Returns name + mentions count.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| window | No | 1d | |
| country | Yes | Source-country ISO 2-letter. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It discloses that returns are named entities with counts, but lacks details on ordering, frequency, or any constraints. Minimal behavioral insight.
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?
Single sentence, very concise. However, it omits important information that could be conveyed without much more text. Balance between conciseness and completeness is reasonable but not optimal.
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, no annotations, and low parameter coverage, description is insufficient. It does not explain return format, ordering, or provide guidance on window parameter usage. Incomplete for effective use.
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 33% (only country has description). Description adds no additional meaning for 'limit' or 'window'; window format is unspecified. Does not compensate for low 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?
Description clearly states the tool returns top mentioned named entities (people, organizations, places) for a country and in the last N hours, with name and mention count. It effectively differentiates from siblings gdelt_search_events and gdelt_tone_timeseries.
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 implies usage for retrieving trending entities, but does not explicitly state when to use this tool versus siblings. No mention of when not to use or context for choosing between tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
3 tool updates
- First observed
gdelt_search_events - First observed
gdelt_tone_timeseries - First observed
gdelt_trending_actors
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