Maap

io.github.codecraf8由 GitHub 账号 codecraf8 发布v0.1.1更新于 Oct 29, 2026

Calibrated numeric estimates with uncertainty from messy records

已验证STDIO仅桌面数据与分析AI 与机器学习

概览

AI 生成的概览

Maap 让助手检索已训练的数值目标，并给出带不确定区间和阈值概率的校准估计。

可以做什么
  • 按关键词和数值类型搜索已训练目标目录，找到查询所需的 target id
  • 针对单个案例和某个目标给出估计，返回中位数、指定分位数、80% 区间以及超过指定阈值的概率
  • 通过 regime、calibration 和 novelty 标记说明该答案的可信程度
适用场景
当你希望得到带明确不确定区间的数值答案而不是单纯猜测时适用，例如根据描述的情形预测价格或数量，或询问某数值超过阈值的可能性。
运行要求
以 npm 包形式通过 npx 在本地运行，需要 Node.js。需要在 MAAP_API_KEY 中提供 API 密钥（从提供方控制台获取），并能访问默认 API 端点；可用 MAAP_BASE_URL 覆盖端点。空闲后的首次调用可能因启动 GPU 容器而耗时数十秒。
安装前请注意
API 密钥通过环境变量传递，属于机密，应避免写入共享配置文件。每次提问都会消耗付费额度，提交的案例信息会发送到提供方 API。答案可能被标记为超出领域、未校准或新颖，此时区间不保证覆盖率。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Maap，将其添加到工作区。
  2. 为需要使用其工具的对话启用该服务。

Desktop only，通过 STDIO。 STDIO 服务会启动本地进程，因此需要 SourceWeft 桌面宿主。

其他 MCP 客户端

参照 仓库 中的启动说明。

README

maap-mcp

maap over MCP: ask for a number, get a calibrated distribution — a median, the range the true value should fall inside, and the probability of crossing a threshold you name.

Two tools:

ToolDoes
list_targetsSearch the 104 trained targets. Call this first — a target id is not guessable
estimateOne case, one target → median, quantiles, intervals, P(value > t), and how calibrated the answer is

Install

Get a key at dash.hitl.systems/keys, then add the server to your client.

Claude Desktop — claude_desktop_config.json:

json
{  "mcpServers": {    "maap": {      "command": "npx",      "args": ["-y", "maap-mcp"],      "env": { "MAAP_API_KEY": "apikey_..." }    }  }}

Claude Code:

bash
claude mcp add maap --env MAAP_API_KEY=apikey_... -- npx -y maap-mcp

Not on npm yet — until it is, install straight from this repo by swapping maap-mcp for github:hitl-systems/maap-mcp in any of the above. The built bundle is committed, so there is nothing to compile.

Cursor — ~/.cursor/mcp.json: the same mcpServers block as Claude Desktop.

VariableRequiredDefault
MAAP_API_KEYyes—
MAAP_BASE_URLnohttps://dash.hitl.systems

Using it

Which maap target predicts flight prices? Estimate the fare for a Vistara economy ticket Delhi → Mumbai, non-stop, booked 9 days out, and tell me the chance it is over ₹10,000.

The agent calls list_targets for the id, then estimate with your case as the state.

Read the median as the answer and the range as what to plan against. For a threshold question, pass thresholds and read P(value > t) — do not compare the median to the threshold yourself; the median says where the middle is, not how likely the threshold is.

An answer also carries how much to trust it: regime (in_domain, or new_target when the model only knows what your examples taught it), calibration ("none" means no correction survived its check, so the range carries no coverage promise), and novelty_flag when the case is unlike anything in training. Known limits are published: dash.hitl.systems/docs/calibration.

Notes

  • One question per call. The HTTP API takes up to 32 under names you choose; a flat tool is the one an agent fills in correctly.
  • The first call after an idle period starts a GPU container and can take tens of seconds. The server waits 120 s and tells the agent to retry rather than failing silently.
  • Each question counts against your allowance. A rejected call costs nothing.
  • Pricing, limits and the full wire format: dash.hitl.systems/docs/api.

MIT.

来源：README.md，提交 e26fd58

工具

2

list_targets

Search the maap catalogue of trained targets. A target is one specific number the model can predict, named by id. Call this FIRST to find the id to pass to `estimate`; ids cannot be guessed. Filter by keyword and by kind of number.

输入参数limitqueryprimitive

estimate

Estimate a number for one case, with calibrated uncertainty. Returns a median (the answer), an 80% range the true value should fall inside about 80 times in 100, the quantiles you asked for, and the probability of crossing any threshold you name. Use the median as the answer, and the range when the decision depends on how wrong it could be. Needs a `target` id from `list_targets`. The first call after an idle period can take tens of seconds.

输入参数state必填levelstarget必填examplesreturn_pmfthresholdsinterval_levels

版本历史

1
  1. v0.1.1最新Oct 21, 2026

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