socrata-mcp-server
Server Details
Search and query government open-data portals (Socrata SODA API).
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- cyanheads/socrata-mcp-server
- GitHub Stars
- 1
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Tool Definition Quality
Average 4.6/5 across 6 of 6 tools scored.
Each tool serves a distinct purpose: portal listing, dataset search, schema metadata, SoQL query, canvas table listing, and canvas SQL query. Descriptions clearly explain when and how to use each, preventing confusion.
The 'socrata_' prefix is consistent. Most tools follow verb_noun (list_portals, find_datasets, get_dataset, query_dataset), but 'dataframe_describe' and 'dataframe_query' invert this pattern, introducing a minor inconsistency.
Six tools cover the essential operations for Socrata open data access and canvas integration without being too few or too many. The scope is well-defined.
The workflow from portal discovery to dataset query and post-query analysis is largely complete. Minor gaps exist, such as missing pagination guidance and a tool for portal metadata beyond listing, but the core operations are well-supported.
Available Tools
6 toolssocrata_dataframe_describeDescribe DataCanvas TablesARead-onlyIdempotentInspect
List registered tables in a DataCanvas session — schema, row count, column names, and registration time. Shows what datasets are available for SQL queries via socrata_dataframe_query. Only meaningful when CANVAS_PROVIDER_TYPE=duckdb is set. Use after socrata_query_dataset spills a large result set to canvas.
| Name | Required | Description | Default |
|---|---|---|---|
| canvas_id | No | Canvas ID returned from socrata_query_dataset. Omit to list all tables visible in the current session. |
Output Schema
| Name | Required | Description |
|---|---|---|
| notice | No | Status message when canvas is not enabled or no tables are registered. Absent when tables are present. |
| tables | Yes | Tables available for SQL queries. Empty when none registered. |
| canvas_id | No | Canvas ID resolved, when canvas is enabled. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and idempotentHint, so the description adds value beyond them by specifying the dependency on duckdb and the typical workflow (after socrata_query_dataset). No contradictions.
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 three sentences with no wasted words. It front-loads the core purpose, then adds context and usage tips efficiently.
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 has an output schema, the description need not detail return values. It sufficiently covers purpose, preconditions, and usage order. It is complete for an agent to decide when to 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?
Schema coverage is 100%, and the description adds meaning to the canvas_id parameter: it is returned from socrata_query_dataset, and omitting it lists all tables. This enriches the schema definition.
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 lists registered tables in a DataCanvas session, specifying schema, row count, column names, and registration time. It distinguishes from sibling tools by mentioning it is used after socrata_query_dataset and only with duckdb.
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 provides clear context: it is meaningful only when CANVAS_PROVIDER_TYPE=duckdb is set, and it should be used after socrata_query_dataset spills a large result set. It could further explicitly state when not to use it, but the guidance is strong.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
socrata_dataframe_queryQuery DataCanvas TableARead-onlyIdempotentInspect
Run SELECT-only SQL against a DataCanvas table populated by socrata_query_dataset. DuckDB infers types from spilled data, so numeric columns that SODA returned as strings become queryable with numeric comparisons (year > 2020, amount < 500). Only works when CANVAS_PROVIDER_TYPE=duckdb is set. Use socrata_dataframe_describe to see registered tables and their schemas.
| Name | Required | Description | Default |
|---|---|---|---|
| sql | Yes | SELECT-only SQL to run against registered canvas tables. DDL, DML, and file-reading functions are rejected. Use table names from socrata_dataframe_describe. | |
| limit | No | Max rows to return (1–10000). Default 1000. | |
| canvas_id | Yes | Canvas ID returned from socrata_query_dataset or socrata_dataframe_describe. |
Output Schema
| Name | Required | Description |
|---|---|---|
| cap | No | The row limit that was applied when capped. |
| sql | Yes | SQL that was executed. |
| rows | Yes | Query result rows. DuckDB may return native JS types (number, boolean, null) for numeric/boolean columns. |
| shown | No | Rows returned in this response when capped. |
| notice | No | Guidance when the SQL returned zero rows. Absent when rows are present. |
| canvas_id | Yes | Canvas ID queried. |
| row_count | Yes | Number of rows returned. |
| truncated | No | True when results were capped at the limit — more rows match the query. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnlyHint, idempotentHint), the description adds valuable behavioral details: DuckDB type inference from spilled data making numeric columns queryable, and that DDL, DML, and file-reading functions are rejected. This gives the agent important expectations about tool execution.
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 two sentences, front-loaded with the core action and a key benefit, followed by a condition and sibling reference. No waste, every word earns its place.
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 an output schema, the description covers purpose, usage condition, behavioral detail, and a pointer to a complementary tool. It is complete given the tool's complexity and the richness of annotations and 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?
Schema coverage is 100%, so baseline is 3. The description repeats the schema's guidance for the 'sql' parameter (use table names from socrata_dataframe_describe) and adds DuckDB inference context, but does not provide new parameter-specific semantics beyond what is already in the schema.
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's function: 'Run SELECT-only SQL against a DataCanvas table populated by socrata_query_dataset.' It specifies the verb (Run SQL), the resource (DataCanvas table), and the condition (SELECT-only). It differentiates from siblings by referencing socrata_query_dataset for population and socrata_dataframe_describe for schema discovery.
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 gives explicit usage context: 'Only works when CANVAS_PROVIDER_TYPE=duckdb is set' and recommends using socrata_dataframe_describe to find tables. It implies when to use (after populating with socrata_query_dataset) but does not explicitly state when not to use or list alternatives, though sibling tools are provided separately.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
socrata_find_datasetsFind Socrata DatasetsARead-onlyIdempotentInspect
Search for datasets across all Socrata-powered government open-data portals, or scope to one portal with the domain parameter. Returns dataset IDs, names, abbreviated column lists, domains, and update timestamps. Use socrata_get_dataset to fetch the full typed column schema before writing queries — columnNames here are preview-only and lack type information.
| Name | Required | Description | Default |
|---|---|---|---|
| only | No | Filter by asset type. Omit to include all types. Usually "datasets" is what you want. | |
| tags | No | Filter by tags (e.g. ["covid19", "permits"]). | |
| limit | No | Number of results to return (1–100). Default 10. | |
| order | No | Sort order. Defaults to relevance. Use updated_at to surface recently-refreshed datasets. | |
| query | No | Full-text search across dataset names and descriptions. Omit to browse without filtering. | |
| domain | No | Scope search to a single portal (e.g. data.seattle.gov, data.cityofnewyork.us). Omit to search all portals. | |
| offset | No | Pagination offset. Default 0. | |
| categories | No | Filter by domain categories (e.g. ["Public Safety", "Transportation"]). |
Output Schema
| Name | Required | Description |
|---|---|---|
| notice | No | Recovery hint when results are empty — echoes filters and suggests how to broaden. Absent on non-empty result pages. |
| results | Yes | Matching datasets. Empty when no results. |
| totalCount | Yes | Total matches before pagination. 0 when empty. |
| effectiveQuery | No | Search query applied, for reference. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint. The description adds behavioral context: it returns dataset IDs, names, abbreviated column lists, domains, and update timestamps, and warns that columnNames are preview-only and lack type information. No contradictions.
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: first states core purpose with options, second gives critical usage guidance linking to sibling. Every sentence earns its place; no wasted words. Front-loaded with the primary action.
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 8 optional parameters, full schema coverage, and presence of output schema, the description covers purpose, return values, and necessary guidance (e.g., use sibling for full schema). It doesn't need to explain return values as output schema exists. A minor gap is no mention of pagination beyond offset/limit, but not critical.
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%, baseline 3. The description adds value by explaining domain scopes to a single portal, order defaults to relevance but suggests updated_at for recent datasets, and only filter 'usually datasets is what you want.'
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 uses specific verbs ('search for datasets') and clearly states the resource (Socrata datasets across all portals or scoped to a domain). It distinguishes from sibling tool socrata_get_dataset by noting that this tool returns preview-only column lists without type information, while the sibling fetches full typed schema.
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 provides clear guidance: use this tool to find datasets, then use socrata_get_dataset to get full schema before writing queries. It explains the domain parameter for scoping and gives tips on sort order. It does not explicitly list when not to use, but the contrast with siblings is sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
socrata_get_datasetGet Dataset SchemaARead-onlyIdempotentInspect
Fetch full metadata and column schema for a Socrata dataset by ID. Returns field names, data types, descriptions, row count, and licensing. Always call this before writing a socrata_query_dataset — the column types determine correct WHERE clause syntax: Number columns accept bare literals (year=2023) while Text columns require single-quoted strings (year='2023').
| Name | Required | Description | Default |
|---|---|---|---|
| domain | No | Portal domain (e.g. data.seattle.gov). Defaults to SOCRATA_DEFAULT_DOMAIN env var or data.seattle.gov. | |
| dataset_id | Yes | Four-by-four dataset ID matching pattern like kzjm-xkqj. Obtain from socrata_find_datasets. |
Output Schema
| Name | Required | Description |
|---|---|---|
| name | Yes | Dataset display name. |
| tags | Yes | Associated tags. |
| domain | Yes | Portal domain hosting this dataset. |
| columns | Yes | Column schema. Computed region columns (:@computed_region_*) are excluded to reduce noise. |
| license | No | License name when available. |
| category | No | Domain category when available. |
| row_count | No | Approximate row count when available. |
| dataset_id | Yes | Four-by-four dataset ID. |
| description | No | Dataset description when available. |
| data_updated_at | No | ISO 8601 timestamp of last data update when available. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true and idempotentHint=true. The description adds valuable behavioral context: returns field names, data types, descriptions, row count, and licensing. Also warns about query implications. No contradiction.
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, front-loaded with purpose. Second sentence provides essential guidance. No redundant information. Every word earns its place.
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 presence of an output schema, description does not need to detail return values. It already mentions key return fields and provides critical usage context. The tool is simple and well-described.
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?
Input schema has 100% coverage with descriptions for both parameters. Description adds beyond schema: explains domain default behavior and source for dataset_id (from socrata_find_datasets). This adds meaningful context, justifying a score above baseline 3.
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 fetches full metadata and column schema for a Socrata dataset by ID. The verb 'Fetch' and resource 'metadata and column schema' are specific. It distinguishes from siblings like socrata_find_datasets (which finds datasets) and socrata_query_dataset (which queries data).
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 explicitly directs 'Always call this before writing a socrata_query_dataset' and explains why: column types determine correct WHERE clause syntax. Provides concrete examples (Number vs Text columns). This is excellent usage guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
socrata_list_portalsList Socrata PortalsARead-onlyIdempotentInspect
List known Socrata-powered government open-data portals with their domain, organization name, and dataset count. Backed by the Discovery API domains catalog. Filtering is client-side substring match on the query parameter. Use this first when you do not know which portal to target, then pass the domain to socrata_find_datasets.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max portals to return (1–200). Default 50. | |
| query | No | Keyword to filter portal names or organization names (case-insensitive substring match). Omit to list all portals. | |
| offset | No | Pagination offset. Default 0. |
Output Schema
| Name | Required | Description |
|---|---|---|
| notice | No | Recovery hint when no portals matched the filter. Absent on non-empty pages. |
| portals | Yes | Matching portals. Empty when no results. |
| totalCount | Yes | Total portals before pagination. 0 when empty. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only, idempotent, and closed world. The description adds that filtering is client-side substring match and mentions the backend API, adding value beyond 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 front-loaded with core purpose, no wasted words. Every sentence adds value.
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, existing output schema, and annotations, the description covers purpose, usage, filtering, backend, and next step completely.
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%, so baseline is 3. The description adds the key detail that query filtering is client-side substring match, enhancing understanding beyond schema descriptions.
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 lists Socrata portals with domain, organization name, and dataset count. It distinguishes from sibling tools by advising to use it first when the portal is unknown.
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?
Explicitly says 'Use this first when you do not know which portal to target, then pass the domain to socrata_find_datasets', providing clear when-to-use and next steps.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
socrata_query_datasetQuery DatasetARead-onlyIdempotentInspect
Execute a SoQL query against any dataset on any Socrata portal. Use the search parameter for quick full-text lookup, or combine select/where/group/having/order for full analytical control. Returns rows plus the assembled SoQL string so you can learn the pattern. All SODA 2.1 row values are strings even for numeric columns — check dataType from socrata_get_dataset to determine correct WHERE quoting: Number columns use bare literals (year=2023), Text columns use single-quoted strings (year='2023'). To enumerate distinct values, use select="col, count(*) as n" with group="col" and order="n DESC". When CANVAS_PROVIDER_TYPE=duckdb and rows fill the limit, results spill to a DataCanvas table for SQL-based analysis.
| Name | Required | Description | Default |
|---|---|---|---|
| group | No | SoQL GROUP BY clause. Requires an aggregate function in select. | |
| limit | No | Max rows to return (1–5000). Default 100. Use with offset for pagination. | |
| order | No | SoQL ORDER BY clause, e.g. "total_deaths DESC" or "date ASC". | |
| where | No | SoQL WHERE clause. Check column dataType from socrata_get_dataset first — Number columns: year=2023, Text columns: year='2023'. Operators: =, !=, >, <, LIKE, IN(...), BETWEEN, IS NULL, starts_with(), contains(), AND, OR, NOT. | |
| domain | No | Portal domain (e.g. data.seattle.gov). Defaults to SOCRATA_DEFAULT_DOMAIN or data.seattle.gov. | |
| having | No | SoQL HAVING clause. Filters on aggregated results, e.g. count > 100. | |
| offset | No | Row offset for pagination. Default 0. | |
| search | No | Full-text search across all text columns ($q). For field-specific filtering, use where instead. | |
| select | No | SoQL SELECT clause — column names, aliases, aggregates: "state, sum(deaths) as total_deaths". Omit for all columns. | |
| canvas_id | No | Optional 10-char DataCanvas token from a prior call. Omit on first call when CANVAS_PROVIDER_TYPE=duckdb to mint a fresh canvas. Large result sets spill here automatically. | |
| dataset_id | Yes | Four-by-four dataset ID (e.g. kzjm-xkqj). Obtain from socrata_find_datasets. |
Output Schema
| Name | Required | Description |
|---|---|---|
| cap | No | The row limit that was applied when capped. |
| rows | Yes | Result rows. Scalar values are strings (SODA 2.1); geo/location columns return nested objects. Use column schema from socrata_get_dataset for type context. |
| shown | No | Rows returned in this response when capped. |
| domain | Yes | Portal domain queried. |
| notice | No | Guidance when the query returned zero rows — suggests narrowing or reviewing the SoQL. Absent on non-empty result sets. |
| canvas_id | No | DataCanvas token when results spilled (requires CANVAS_PROVIDER_TYPE=duckdb). Pass to socrata_dataframe_query for SQL over the full result set. |
| row_count | Yes | Rows returned in this response. |
| truncated | No | True when rows filled the limit — more rows match (see total_count). Spills to canvas when enabled. |
| dataset_id | Yes | Dataset ID queried. |
| total_count | No | Total matching rows when result is truncated (row_count < total_count). Absent when the full result fits. |
| assembled_query | Yes | SoQL clauses assembled for this request — useful for learning the syntax. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true and idempotentHint=true, and description confirms read-only nature ('Execute a SoQL query'). Adds behavioral details beyond annotations: returns assembled SoQL string, all row values are strings, spill behavior to DataCanvas. No contradiction.
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?
Description is a single paragraph with five sentences covering key points without excessive verbosity. It front-loads the main purpose and then adds usage guidance, behavioral notes, and edge cases. Could be slightly more structured (e.g., bullet points for quoting rules), but remains concise and effective.
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 complexity (11 parameters, output schema exists, annotations present), the description covers all essential aspects: purpose, dual usage modes, output details, quoting nuance, distinct value pattern, spill behavior, and integration with other tools. It is complete and leaves no critical gaps.
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?
Input schema covers 100% of parameters with descriptions. The description adds critical extra semantics: quoting rules for Number vs Text columns, pattern for distinct values using group and count(*), and spill behavior for large results. This enriches the schema descriptions meaningfully.
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 executes a SoQL query against any Socrata dataset, with specific verb (Execute a SoQL query) and resource (any dataset on any Socrata portal). It distinguishes from siblings by detailing two usage modes (search vs full SoQL) and mentioning output specifics (rows plus assembled SoQL string), making the purpose 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?
Provides clear guidance: when to use search parameter for quick full-text lookup versus combining select/where/group/having/order for analytical control. Advises checking dataType from socrata_get_dataset for correct quoting. Mentions spill behavior for large results. While not explicitly listing when not to use or alternatives, the context with sibling tools implies separation of concerns.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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