NIFC Wildfire Data
Server Details
Active wildfire incidents from the National Interagency Fire Center
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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.
Tool Definition Quality
Average 3.5/5 across 3 of 3 tools scored.
Each tool has a clearly distinct purpose: get_active_fires returns incident-level data, get_fire_perimeters provides geographic boundary information, and get_fire_stats offers aggregate statistics. There is no functional overlap between these three tools, making them easily distinguishable for an agent.
All tools follow a consistent verb_noun pattern with 'get_' prefix followed by a descriptive noun phrase (active_fires, fire_perimeters, fire_stats). The naming convention is perfectly uniform across all three tools.
With only 3 tools, the server feels somewhat thin for a comprehensive wildfire data service. While the tools cover distinct aspects of wildfire information, additional tools for historical data, weather integration, or fire behavior modeling would make the surface more complete.
The tools provide good coverage of current wildfire data (incidents, perimeters, statistics), but there are notable gaps. Missing operations include historical fire data retrieval, fire weather information, evacuation zone data, or fire progression tracking, which would be expected in a comprehensive wildfire data service.
Available Tools
3 toolsget_active_firesAInspect
Get current active wildfire incidents from NIFC.
Returns data on active wildfires including name, location, size, and
containment status. Data is updated frequently during fire season.
Args:
state: Two-letter US state abbreviation to filter by (e.g. 'CA', 'OR').
min_acres: Minimum fire size in acres to include (e.g. 100 for fires over 100 acres).
limit: Maximum number of fires to return (default 50).| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| state | No | ||
| min_acres | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Mentions data update frequency ('frequently during fire season') but lacks other behavioral details like rate limits, caching behavior, or data latency since no annotations exist.
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?
Well-structured with purpose first, followed by return value description and Args section; no redundant text though the docstring-style Args formatting could be more integrated.
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?
Adequately complete given the simple schema and existence of output schema; mentions key return fields (name, location, size, containment) without over-explaining what the structured output schema already covers.
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?
Excellent compensation for 0% schema description coverage by documenting all three parameters with clear semantics, expected formats, and concrete examples (e.g., 'CA', 'OR', 100).
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?
Clearly states it retrieves active wildfire incidents from NIFC with specific return fields, though it doesn't explicitly differentiate from sibling tools get_fire_perimeters and get_fire_stats.
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?
Provides no guidance on when to use this tool versus alternatives or when filtering parameters are appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_fire_perimetersAInspect
Get fire perimeter data for active or recent wildfires.
Returns perimeter boundaries and associated metadata. Useful for
understanding the geographic extent of fires.
Args:
fire_name: Name of a specific fire to look up (case-insensitive partial match).
state: Two-letter US state abbreviation to filter by.| Name | Required | Description | Default |
|---|---|---|---|
| state | No | ||
| fire_name | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses data scope ('active or recent') and matching behavior ('case-insensitive partial match') but omits auth requirements, rate limits, or error handling.
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?
Appropriately brief and front-loaded; the Args section is slightly informal but efficiently conveys necessary parameter semantics 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?
Adequate for the low complexity (2 optional params); briefly acknowledges return values despite presence of output schema.
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?
Effectively compensates for 0% schema description coverage by documenting both parameters, including critical behavioral detail about partial matching for fire_name.
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?
Clearly states it retrieves fire perimeter boundaries for active/recent wildfires, distinguishing it from sibling tools via the specific resource type (perimeters vs active fires/stats).
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?
Provides implied usage context ('Useful for understanding geographic extent') but lacks explicit guidance on when to choose this over get_active_fires or get_fire_stats.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_fire_statsBInspect
Get wildfire statistics summary including total fires and acres burned.
Returns aggregate statistics from active incident data. When no year is
specified, returns current year statistics.
Args:
year: Year to get statistics for (e.g. 2025). Defaults to current year.| Name | Required | Description | Default |
|---|---|---|---|
| year | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Adds data provenance context ('from active incident data') and default year behavior, but lacks other behavioral traits like rate limits or cache details.
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?
Front-loaded with purpose, appropriately brief; Args section is necessary given schema lacks descriptions.
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?
Sufficient for low complexity (1 optional param); presence of output schema excuses lack of return value documentation.
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?
Effectively compensates for 0% schema description coverage by documenting the year parameter's purpose, type hint (e.g. 2025), and default behavior.
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?
Clear specific action (get wildfire statistics) and resource (total fires/acres), implicitly distinct from siblings (aggregate stats vs active fires/perimeters).
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 choose this over get_active_fires or get_fire_perimeters; only parameter-level guidance provided.
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.
Discussions
No comments yet. Be the first to start the discussion!