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melaodoidao

Data.gov MCP Server

by melaodoidao
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Data.gov MCP Server

An MCP server for accessing data from Data.gov, providing tools and resources for interacting with government datasets.

Installation

  1. Install the package globally:

    npm install -g @melaodoidao/datagov-mcp-server

  2. Configure the MCP Server:

    • Add the following entry to your cline_mcp_settings.json file (usually located in ~/Library/Application Support/Code/User/globalStorage/saoudrizwan.claude-dev/settings/ on macOS):

       {
   "mcpServers": {
     "datagov": {
       "command": "datagov-mcp-server",
       "args": [],
       "env": {}
     }
   }
 }

    • If you are using the Claude Desktop app, add the entry to ~/Library/Application Support/Claude/claude_desktop_config.json instead.

Related MCP server: datagovma-mcp

Usage

This server provides the following tools:

  • package_search: Search for packages (datasets) on Data.gov.

  • package_show: Get details for a specific package (dataset).

  • group_list: List groups on Data.gov.

  • tag_list: List tags on Data.gov.

It also provides the following resource template:

  • datagov://resource/{url}: Access a Data.gov resource by its URL.

You can use these tools and resources with Cline by specifying the server name (datagov-mcp-server) and the tool/resource name.

Contributing

Contributions are welcome! Please feel free to submit issues or pull requests.

License

MIT License

Available Tools

4 tools
group_listB

List groups on Data.gov

ParametersJSON Schema
NameRequiredDescriptionDefault
all_fieldsNoReturn all fields
limitNoMaximum number of results
offsetNoOffset for results
order_byNoField to order by

TDQS

B3.1/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden for behavioral disclosure. It mentions 'List groups' which implies a read-only operation, but doesn't specify authentication requirements, rate limits, pagination behavior, or what happens when no groups exist. For a tool with zero annotation coverage, this is insufficient.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, clear sentence with zero wasted words. It's appropriately sized for a simple list operation and front-loads the essential information immediately.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a list operation with full schema coverage but no annotations or output schema, the description provides the basic purpose but lacks behavioral context. It's minimally adequate but doesn't compensate for the missing annotation coverage about read-only status, authentication, or response format.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already fully documents all four parameters. The description doesn't add any parameter-specific information beyond what's in the schema, which meets the baseline expectation when schema coverage is complete.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('List') and resource ('groups on Data.gov'), making the purpose immediately understandable. It doesn't distinguish from sibling tools like 'tag_list' which also lists resources, but it's specific enough to understand what it does.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided about when to use this tool versus alternatives like 'tag_list' or 'package_search'. The description only states what it does without context about appropriate use cases, prerequisites, or limitations.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

package_showB

Get details for a specific package (dataset)

ParametersJSON Schema
NameRequiredDescriptionDefault
idYesPackage ID or name

TDQS

B3.1/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states this is a 'Get' operation, implying it's likely read-only, but doesn't confirm safety aspects like whether it requires authentication, has rate limits, or what happens if the package doesn't exist. More context is needed for a mutation-aware agent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the core purpose without any wasted words. It's appropriately sized for a simple tool with one parameter, making it easy to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's low complexity (one parameter, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose but lacks details on usage context, behavioral traits, or output format, which could hinder an agent in more complex scenarios.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 100%, with the 'id' parameter fully documented in the schema. The description adds no additional parameter details beyond implying the tool fetches details for a package, which aligns with the schema. This meets the baseline for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with a specific verb ('Get details') and resource ('package (dataset)'), making it immediately understandable. It doesn't explicitly differentiate from sibling tools like 'package_search' or 'group_list', which prevents a perfect score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives like 'package_search' or 'group_list'. It lacks context about prerequisites, such as needing a specific package ID, and doesn't mention any exclusions or complementary tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

tag_listC

List tags on Data.gov

ParametersJSON Schema
NameRequiredDescriptionDefault
all_fieldsNoReturn all fields
queryNoSearch query for tags

TDQS

C2.9/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states 'List tags' but doesn't describe any behavioral traits such as pagination, rate limits, authentication needs, or what the output looks like (e.g., format, structure). This is a significant gap for a tool with no annotation coverage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that directly states the tool's purpose without any wasted words. It's appropriately sized and front-loaded, making it easy to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of annotations and output schema, the description is incomplete. It doesn't address behavioral aspects like output format, error handling, or usage context, which are crucial for an agent to invoke the tool correctly. This is inadequate for a tool with no structured support.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description adds no parameter semantics beyond what the input schema provides, which has 100% coverage with clear descriptions for both parameters. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, as the description doesn't compensate or add extra meaning.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('List') and resource ('tags on Data.gov'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'group_list' or 'package_search', which also list resources, so it doesn't fully distinguish its specific scope beyond the resource type.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives like 'package_search' or 'group_list'. There's no mention of context, prerequisites, or exclusions, leaving the agent to infer usage based on tool names alone.

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.

  1. 4 tool updatesv1.0.0
    • First observedgroup_list
    • First observedpackage_search
    • First observedpackage_show
    • First observedtag_list
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TDQS

B3.2/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose targeting different resources: groups, packages (datasets), and tags. The actions (list, search, show) are well-defined and non-overlapping, making it easy for an agent to select the right tool without confusion.

Naming Consistency5/5

All tool names follow a consistent snake_case pattern with a clear verb_noun structure (e.g., group_list, package_search). This predictability enhances readability and usability across the tool set.

Tool Count3/5

With only 4 tools, the set feels thin for a data portal server, lacking operations like create, update, or delete for resources. While the tools cover basic read/search functions, the scope could be expanded for more comprehensive coverage.

Completeness2/5

The tool surface is severely incomplete for a data management domain, missing essential CRUD operations (e.g., no create_package, update_package, delete_package) and other common actions like resource_show for groups or tags. This will likely cause agent failures when trying to perform full lifecycle tasks.

Maintenance

ActivityInactive
ResponsivenessSyncing

Resources

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