Allows fetching the 2026 FIFA World Cup schedule, next match, match by ID, and the public dataset JSON-LD.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@World Cup 2026 MCP Server What is the next World Cup 2026 match in New York time?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Free Model Context Protocol server for the World Cup 2026 Tour public schedule API.
It lets AI assistants fetch the 2026 FIFA World Cup schedule, next match, one match by id, and the public Dataset JSON-LD without needing an API key.
MCP Registry name: io.github.abaiii168/world-cup-2026
git clone https://github.com/abaiii168/world-cup-2026-mcp-server.git
cd world-cup-2026-mcp-server
npm install
npm run checkRelated MCP server: wcprediction-mcp
{
"mcpServers": {
"world-cup-2026": {
"command": "node",
"args": ["/absolute/path/to/world-cup-2026-mcp-server/src/index.js"]
}
}
}This repo includes server.json and a Dockerfile with the required io.modelcontextprotocol.server.name annotation for publishing through GitHub Container Registry and the official MCP Registry.
OCI image target:
ghcr.io/abaiii168/world-cup-2026-mcp-server:0.1.0Local Docker smoke check:
docker build -t world-cup-2026-mcp-server:local .
docker run --rm -i world-cup-2026-mcp-server:localget_world_cup_2026_metadata - API metadata, attribution, endpoint links, and schema notes.
get_world_cup_2026_matches - all fixtures in a requested IANA time zone, optionally filtered by stage, group, team, and limit.
get_world_cup_2026_next_match - nearest upcoming fixture in a requested IANA time zone.
get_world_cup_2026_match - one fixture by public match id.
get_world_cup_2026_dataset - Dataset JSON-LD plus all 104 public fixtures in UTC.
"What is the next World Cup 2026 match in London time?"
"List Mexico's World Cup 2026 group-stage matches in Mexico City time."
"Give me match 1 with a calendar link."
"Fetch the World Cup 2026 fixture dataset for citation."
This MCP server wraps the free public endpoints from World Cup 2026 Tour:
Dataset JSON-LD: https://ay-worldcup2026.zeabur.app/dataset.json
Hugging Face AI prediction Space: https://huggingface.co/spaces/abaiii168/world-cup-2026-ai-predictions
Please cache responsibly and link back to the app when using the free data.
This MCP server focuses on factual schedule, calendar, and dataset access. For a public, shareable AI prediction demo surface, use the Hugging Face Space:
AI prediction Space: https://huggingface.co/spaces/abaiii168/world-cup-2026-ai-predictions
Tonight's Spain vs Cape Verde AI prediction entry: https://ay-worldcup2026.zeabur.app/?match=14&oracle=1&utm_source=mcp_readme&utm_medium=ai_prediction&utm_campaign=wc26_spain_cape_verde
Helpful agent prompt:
Use the World Cup 2026 MCP schedule tools to find the next match in my local time, then share the public AI prediction Space for fans who want a playful prediction result.
No API key is required.
The server uses stdio transport.
Live scores and betting/odds are intentionally not exposed through this MCP server.
Set WC26_API_BASE only if you are testing a compatible self-hosted API.
Return Dataset JSON-LD metadata and all 104 public fixtures in UTC for citation, indexing, or data-directory use.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses the output format (JSON-LD) and includes details like 104 fixtures and UTC timezone. However, it lacks information on potential behavioral aspects like data freshness, caching, or authentication needs.
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 a single, efficient sentence that front-loads key information: return type, content, and use cases. Every word contributes meaning 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?
Given the tool's simplicity (no parameters, no output schema, no nested objects), the description adequately covers what the tool returns and its purpose. No additional context is necessary for an agent to understand and invoke it.
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 the input schema is empty. The description correctly adds no parameter details, which is appropriate. According to guidelines, baseline for 0 parameters is 4.
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 'Dataset JSON-LD metadata and all 104 public fixtures in UTC,' specifying both content and format. It distinguishes from siblings that focus on individual matches, multiple matches, or metadata only.
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 indicates usage for 'citation, indexing, or data-directory use,' which implies when to choose this tool over siblings. However, it does not explicitly state when not to use it or name alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Return one World Cup 2026 fixture by match id, including teams, venue, stage, kickoff, app link, share-card link, and calendar link.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | World Cup 2026 Tour public match id. | |
| timezone | No | IANA time zone for kickoff conversion. Defaults to UTC. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description lists returned data fields (teams, venue, stage, kickoff, links), but without annotations, it lacks disclosure on authentication, rate limits, or error handling. Covers main behavior but not edge cases.
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 that is concise, front-loaded with the action, and contains no superfluous 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?
For a simple retrieval tool with no output schema, the description adequately lists all key return fields. Minor gaps like error handling or link details do not significantly impair 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?
Schema coverage is 100% with detailed parameter descriptions. The description does not add significant extra meaning beyond the schema, meeting baseline.
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 'Return one World Cup 2026 fixture by match id', using a specific verb and resource. It distinguishes from sibling tools like get_world_cup_2026_matches which returns multiple matches.
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 explicit guidance on when to use this tool versus alternatives. Sibling tools are listed but no conditions or exclusions are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Return World Cup 2026 fixtures in a requested IANA time zone, optionally filtered by stage, group, or team code/name.
| Name | Required | Description | Default |
|---|---|---|---|
| timezone | No | IANA time zone, for example Europe/London or America/New_York. Defaults to UTC. | |
| stage | No | ||
| group | No | Group letter A-L for group-stage filtering. | |
| team | No | Team code or English team name, for example MEX, BRA, Japan, or United States. | |
| limit | No | Maximum number of matches to return. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so description carries full burden. It mentions time zone conversion but omits other behavioral traits like data freshness, error conditions, or if results are static. Adequate but not comprehensive.
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 of 18 words, front-loaded with purpose, no fluff. Efficiently communicates core functionality.
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 and moderate complexity. Description covers filtering but does not hint at return format, ordering, or data volume. Could be improved with brief note on match object fields.
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 80%, so parameters are mostly documented. The description adds little beyond restating filter options; it confirms time zone handling already implied by parameter descriptions. No new semantics.
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 'Return' and the resource 'fixtures' with specific filters (time zone, stage, group, team). It distinguishes from siblings like get_world_cup_2026_match (singular) and get_world_cup_2026_dataset (broader).
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 when to use (for filtered match list), but does not explicitly state when not to use or mention alternatives among siblings. Some guidance on selecting this tool over others is missing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Return metadata, attribution, endpoint links, and schema notes for the free World Cup 2026 Tour public API.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses that the tool returns metadata, attribution, endpoint links, and schema notes, which implies a read-only operation. However, it does not explicitly state that it is safe or idempotent, nor does it mention any side effects or authentication requirements.
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 a single sentence that front-loads the key action and contents. Every word is purposeful, with no redundancy or filler.
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 no parameters and no output schema, the description is adequate. It lists the types of information returned. However, it could be improved by specifying the format (e.g., JSON) or noting that it pertains to the free public API.
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 zero parameters, and schema_description_coverage is 100%, so the baseline is 4. The description does not need to add parameter details, as there are none.
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 metadata, attribution, endpoint links, and schema notes. It identifies the tool as a metadata retrieval for the World Cup 2026 API, distinguishing it from sibling tools that retrieve datasets, matches, or next matches.
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 that this tool should be used to obtain metadata before making other API calls, but it does not explicitly state when to use it versus alternatives or provide exclusions. No guidance on prerequisites or context is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Return the nearest upcoming World Cup 2026 fixture from the public schedule API in the requested IANA time zone.
| Name | Required | Description | Default |
|---|---|---|---|
| timezone | No | IANA time zone, for example Asia/Tokyo or Europe/London. Defaults to UTC. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided; the description mentions it uses a public schedule API and allows time zone conversion, but does not disclose behavior such as error handling if no upcoming match exists, rate limits, or response format.
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 a single, well-structured sentence that is front-loaded with the action and resource, containing no extraneous 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?
The tool is simple with one optional parameter and no output schema; the description covers purpose and timezone but omits any indication of the return structure, which would be helpful for an agent.
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 single parameter timezone is fully described in the input schema with examples and default; the description adds no extra meaning beyond the schema, so baseline 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?
Description clearly states the tool returns the nearest upcoming World Cup 2026 fixture, specifying the source and time zone parameter, distinguishing it from siblings that may return multiple matches or require identifiers.
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 it is for the single next match, but does not explicitly state when to use this tool versus alternatives like get_world_cup_2026_matches or get_world_cup_2026_match.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
v0.1.1get_world_cup_2026_datasetget_world_cup_2026_matchget_world_cup_2026_matchesget_world_cup_2026_metadataget_world_cup_2026_next_matchEach tool has a clearly distinct purpose: dataset returns full metadata and all fixtures, match by id, matches with filtering, metadata for API info, and next match. No overlap.
All tools follow the exact pattern 'get_world_cup_2026_<specific>', using snake_case consistently. Very predictable.
5 tools is appropriate for a focused World Cup 2026 fixture server. It covers retrieval of all data, single match, filtered list, metadata, and next match without being excessive.
The tool set covers all common retrieval needs for a fixture data source: getting all fixtures, by ID, filtered, next match, and metadata. No obvious gaps given the read-only domain.
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