MCP server

Georgia Civic Data Official

org.georgiacivicdata/georgia-civic-data

Checked 26 Oct 2026, 08:29 UTC · Connected to it and listed its tools

Georgia education, Census, and immigration data: query, filter, aggregate, and link datasets.

Website Source

At a glance

Type

MCP server

Publisher

georgiacivicdata.org (verified by the MCP Registry)

Status

Working at last check

Tools

13

Token cost

About 7,476 tokens per request

Sets up in

Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok

Last checked

26 Oct 2026, 08:29 UTC

Connect it to your agent

Add to CursorAdd to VS CodeVS Code Insiders

Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.

Claude Code

claude mcp add --transport http georgia-civic-data https://mcp.georgiacivicdata.org/mcp/

Claude Desktop

Settings → Connectors → Add custom connector, and paste the URL.

Codex (config.toml)

[mcp_servers.georgia-civic-data]
url = "https://mcp.georgiacivicdata.org/mcp/"

Gemini CLI

{"mcpServers":{"georgia-civic-data":{"httpUrl":"https://mcp.georgiacivicdata.org/mcp/"}}}

Cursor

{"mcpServers":{"georgia-civic-data":{"url":"https://mcp.georgiacivicdata.org/mcp/"}}}

VS Code

{"servers":{"georgia-civic-data":{"type":"http","url":"https://mcp.georgiacivicdata.org/mcp/"}}}

Antigravity

agy mcp add georgia-civic-data https://mcp.georgiacivicdata.org/mcp/

ChatGPT

Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.

OpenAI API (Responses tools)

{"type":"mcp","server_label":"georgia-civic-data","server_url":"https://mcp.georgiacivicdata.org/mcp/","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"georgia-civic-data","server_url":"https://mcp.georgiacivicdata.org/mcp/"}

Tools

• aggregate ~1348 tokens
  A summary of one dataset computed on the server: one small row per group instead of raw rows. `agg` is avg, sum, min, max, count, or weighted_rate. `metric` is the figure to summarize (default: the dataset's key_metric; ignored for count). `group_by` lists columns to group by (year, code columns lik
• describe_dataset ~691 tokens
  The full schema of one dataset: every column (type, role, unit, value range, what a NULL means), the exact `filters` with their valid values (the keys query_dataset and aggregate accept), how the code columns join to the lookup tables (`foreign_keys`), example queries, usage notes, limitations, and
• describe_dimension ~278 tokens
  The schema of one shared lookup table (a dimension: districts, schools, counties, tracts, block_groups, or demographics): its key columns (schools use district_code plus school_code together), the attribute columns a join adds, the keys that link to other data (`link_keys`: districts.district_census
• distinct_values ~546 tokens
  The distinct values of one filter column of a dataset, to learn valid filter values before query_dataset. Most useful for code columns (district_code, school_code, county_fips, demographic) and category columns without a fixed list in describe_dataset, where a wrong guess returns an empty page rathe
• get_contract ~367 tokens
  The full data contract of one dataset (kind='topic') or lookup table (kind='dimension'): the machine-readable document, in the Open Data Contract Standard (ODCS) v3.2 format, that defines its columns, keys, units, quality checks, source, and limitations. fmt='yaml' (default) returns the document as
• get_dimension ~279 tokens
  The rows of one shared lookup table: district, school, county, census tract, or demographic codes with their names and attributes, in key order so paging is stable. describe_dimension gives the schema. Pages are small; when `truncated` is true, `bulk_export` gives the REST API address for the full t
• link_query ~482 tokens
  Runs one read-only SQL query across datasets, for analysis the per-dataset filters cannot express, such as joining education, Census, or immigration figures to a lookup table or to each other on shared geography (immigration and county-level Census data share county_fips). The dialect is DuckDB SQL
• link_tables ~328 tokens
  The tables link_query can read and the keys that join them: datasets to lookup tables to Census geography. With no arguments, a short index: each dataset's `table` name for SQL (e.g. 'education.attendance', its default detail level), what one row is (`grain`), detail levels, and join keys, plus each
• list_datasets ~330 tokens
  The catalog: every published Georgia dataset and the shared lookup tables (district, school, county, census tract, and demographic names). By default each dataset is compact: its key (main_topic/sub_topic/topic), title, one-line summary, and first and last year. detail='full' adds detail levels, yea
• lookup_school_zone ~919 tokens
  Which Georgia public school attendance zones (elementary, middle, high) contain a place, or (attendance_rules=true) how attendance zones work in Georgia. Give exactly one of: lat and lon; an address (located with the U.S. Census Geocoder, an outside service); a 2020 census tract_geoid (every zone co
• query_dataset ~1174 tokens
  Rows of one dataset, filtered, with the district, school, county, and demographic names joined in. `filters` takes code columns and category columns (describe_dataset's `filters` lists the exact keys and valid values). Use `year` or `year_min`/`year_max`, not both. `detail` picks what one row descri
• resolve_entity ~500 tokens
  Turns a place or demographic name or code into the code the data uses (district_code, school_code, county_fips, or demographic) with its label, e.g. 'Atlanta Public Schools' or 'Fulton'. A guessed code otherwise returns an empty page. `kind` is district, school, county, or demographic; 'Fulton' as a
• search_datasets ~234 tokens
  Keyword search over the catalog: dataset names, titles, descriptions, tags, and column names and descriptions. Returns short dataset summaries ranked by relevance, with the fields that matched, plus `dimension_matches` when the words also match a lookup table (e.g. 'district'). Acronyms work, includ

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