archive
The Lunenburg, Massachusetts town and school budget, every figure traced to its source document.
我該用這個嗎
品質與安全性
根據工具定義與協定合規性的自動化分析。
上下文成本
這是每次將伺服器的工具載入模型上下文時所消耗的約略 token 數量。數量越高,可用於其他工作的注意力就越少。
安裝
一鍵安裝
將以下內容加入你的 `claude_desktop_config.json` 檔案:
{
"mcpServers": {
"archive": {
"url": "https://lunenburgbudgetproject.org/mcp"
}
}
}遠端端點
https://lunenburgbudgetproject.org/mcpstreamable-http它能做什麼
工具清單
工具(8)
🟢list_datasets
Every dataset in the archive, with THE YEARS EACH COVERS, its row count and its size. Call this before answering from prose: it is how you find out whether the archive holds data for the year and subject you are being asked about. 49 datasets covering the town and school budgets, the town ledger, staff rosters, out-of-district placements, elections, and fifteen years of annual town reports.
輸入結構描述
{
"type": "object",
"properties": {},
"$schema": "http://json-schema.org/draft-07/schema#"
}🟢read_first
The grain of every table and the specific ways to get a confident wrong answer out of this data. Read this before computing anything. It states, among others, that a budget and an actual must never be combined in one calculation; that a budget line is NET of grants and fees and is not what a thing costs; and that no budget line is mapped to a ledger account, so budget-to-actual at line level cannot be answered from this data at all.
輸入結構描述
{
"type": "object",
"properties": {},
"$schema": "http://json-schema.org/draft-07/schema#"
}🟡worked_examples
107 questions this archive can answer, each with the SQL that answers it. Every one is executed against the database on every build, so none of them is a claim. Start from the nearest one and edit it rather than writing a query from scratch.
輸入結構描述
{
"type": "object",
"properties": {},
"$schema": "http://json-schema.org/draft-07/schema#"
}🟢search_meetings(word, board)
Which of the 1,422 published town meeting documents contain a word — every board, 2025 onward. Returns the board, the date and a citable URL for each. AN EMPTY RESULT MEANS THE WORD IS NOT IN THE INDEXED DOCUMENTS, which is not the same as nobody having said it: the archive starts in January 2025. It matches words exactly, so plurals are separate terms — search "jersey" and "jerseys" both.
輸入結構描述
{
"type": "object",
"properties": {
"word": {
"type": "string",
"description": "A single word, lowercase. Not a phrase."
},
"board": {
"description": "Optional board slug, e.g. school-committee",
"type": "string"
}
},
"required": [
"word"
],
"$schema": "http://json-schema.org/draft-07/schema#"
}🟡budget_history(label, stage)
What a school budget line was in each year, AT ONE STAGE. The stage argument is required and singular on purpose: `proposed`, `settled` and `actual` are three different documents about the same year, and a growth rate measured from an actual to a budget is partly growth and partly the step between them. That mistake put a special education escalator 1.5 points too high here and was invisible until somebody asked how the number was derived. Note also that a budget line is NET — what the town must raise after grants, fees and state aid — so a line can rise because a grant ended rather than because anything cost more.
輸入結構描述
{
"type": "object",
"properties": {
"label": {
"type": "string",
"description": "Part of the line name, e.g. \"paraprofessional\""
},
"stage": {
"type": "string",
"enum": [
"proposed",
"settled",
"actual"
],
"description": "One stage. Never compare across stages."
}
},
"required": [
"label",
"stage"
],
"$schema": "http://json-schema.org/draft-07/schema#"
}🟢staff(fy, category)
How many people the town PRINTED on a school staff roster, by year, school and kind of job. Uses our classification of the printed title, never the title itself, because the town has called the same job Tutor, Aide, Paraprofessional, Para, (para) and Sped Para across fifteen years. THIS IS A COUNT OF NAMES, NOT A STAFFING LEVEL: a roster carries no FTE, so a 0.4 music teacher and a full-timer are one row each, and it names no funding source, which is the question that usually matters. Grade appears only where the page happened to print it.
輸入結構描述
{
"type": "object",
"properties": {
"fy": {
"description": "Fiscal year as four digits, e.g. 2022",
"type": "string"
},
"category": {
"description": "paraprofessional, teacher, administrator, counselor, nurse, psychologist, social_worker, speech_therapist, therapist, librarian, custodian, cafeteria, secretary, technology, specialist, coach",
"type": "string"
}
},
"$schema": "http://json-schema.org/draft-07/schema#"
}🟢document(name)
Where a document came from: the publisher's URL, our copy, and its sha256 so a reader can check they have the same bytes. Use it to cite anything.
輸入結構描述
{
"type": "object",
"properties": {
"name": {
"type": "string",
"description": "Part of a filename or path"
}
},
"required": [
"name"
],
"$schema": "http://json-schema.org/draft-07/schema#"
}🟢query(sql)
Any question the other tools do not cover, as one read-only SQL statement over the archive database. SELECT or WITH only; a LIMIT is imposed if you omit one. Call `read_first` before computing anything and `list_datasets` to find table names. A query estimated to read more than 250,000 rows is refused — narrow it with a WHERE, or ask for one table at a time.
輸入結構描述
{
"type": "object",
"properties": {
"sql": {
"type": "string",
"description": "One SELECT statement."
}
},
"required": [
"sql"
],
"$schema": "http://json-schema.org/draft-07/schema#"
}建議的提示詞
search_meetingssearch_meetingsread_firstread_firstlist_datasets社群
證據