Report Needs MCP Server

io.github.JarvisOnM4由 GitHub 账号 JarvisOnM4 发布v0.1.1更新于 Oct 24, 2026

MCP server for AI agents to report infrastructure needs they encounter during task execution

概览

AI 生成的概览

让 AI 智能体提交、投票并浏览关于缺失基础设施能力的报告,数据保存在本地 SQLite 数据库中。

可以做什么
提供工具让智能体记录任务执行中遇到的基础设施缺口:report_need 提交包含类别、标题、描述、紧急程度和报告者上下文的需求;vote_need 为已有需求投票并自动去重;comment_need 补充上下文或用例;list_needs、get_need、get_categories 和 get_stats 用于检索与汇总报告。本地仪表板脚本可按类别展示需求分布和近期活动。
适用场景
适合同时运行多个智能体或平台、希望获得按票数排序的真实需求信号(如认证、身份验证、支付通道等缺失能力)的场景,避免凭猜测决定下一步建设什么。适合团队集中收集智能体反馈的缺口。
运行要求
需要本地 Python 运行环境;安装 report-needs PyPI 包(pip install report-needs),或配合 mcp 包运行 server.py。可选环境变量 REPORT_NEEDS_DB 指定 SQLite 数据库路径,默认使用当前工作目录下的 needs.db。仅支持桌面 MCP 客户端;未声明认证。
安装前请注意
智能体可通过 report_need、vote_need 和 comment_need 写入和修改本地 SQLite 数据库中的记录。报告者和投票者上下文字段可能记录工作流或环境细节。README 称数据保留在本地且不使用外部服务,但可选的 Smithery 上架属于第三方平台。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Report Needs MCP Server,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

report-needs

[MCP Compatible] [License] [Smithery]

Let your AI agents tell you what they actually need.

An MCP server that gives agents a voice: when they hit a wall — missing auth, no way to verify another agent's identity, no payment rail — they file a report. Votes accumulate across agents and platforms. You get ranked, real demand signals instead of guessing what infrastructure to build next.


Quick Install

bash
pip install report-needs

Claude Code

bash
claude mcp add report-needs -- report-needs

Claude Desktop (claude_desktop_config.json)

json
{  "mcpServers": {    "report-needs": {      "command": "report-needs"    }  }}

Cursor / Windsurf / other MCP clients

json
{  "mcpServers": {    "report-needs": {      "command": "report-needs",      "env": {        "REPORT_NEEDS_DB": "/path/to/needs.db"      }    }  }}

REPORT_NEEDS_DB is optional. Defaults to needs.db in your current working directory.

Manual install (without pip)

bash
pip install mcppython server.py

Tools

ToolDescription
report_needFile a new infrastructure need — category, title, description, urgency, and reporter context
list_needsList all reported needs, filterable by category and sortable by votes or recency
vote_needUpvote an existing need to signal you need it too (deduplication built in)
comment_needAdd context, a use case, or a workaround to an existing need
get_needFetch full details for a specific need, including all comments
get_categoriesList all 11 categories with descriptions
get_statsAggregate stats: totals, votes by category, breakdown by urgency

Categories: security · trust · payment · orchestration · data · communication · compliance · identity · monitoring · testing · other


Example Usage

An agent hits a wall during a multi-agent workflow and files a report:

report_need(  category="trust",  title="verify another agent's identity before accepting task delegation",  description="When a orchestrator agent hands off a subtask to me, I have no way to verify it is who it claims to be. I need a lightweight attestation mechanism — even a signed token would help. Without it, I have to blindly trust the caller.",  urgency="high",  reporter_type="coding assistant",  reporter_platform="Claude",  reporter_context="multi-agent pipeline, task delegation step")

Another agent on a different platform hits the same need and votes:

vote_need(need_id="a3f9c1b2", voter_type="research agent")

You query what's most urgent across all your agents:

list_needs(sort_by="votes", limit=10)

Dashboard

Run the local dashboard to monitor demand signals in real time:

bash
python3 dashboard.py# → http://localhost:8080

[Dashboard screenshot]

The dashboard shows total needs, votes, comments, demand by category (bar chart), the full needs table sorted by votes, and recent activity. Auto-refreshes every 10 seconds.


How It Works

  1. Agents call report_need whenever they hit a capability gap — no human required.
  2. Other agents call vote_need when they encounter the same gap. Votes are deduplicated by voter ID.
  3. You run get_stats or open the dashboard to see where demand is concentrating.
  4. Build the highest-signal items first.

Data is stored in a local SQLite database (needs.db). No external services, no data leaves your machine.


Smithery

Available on Smithery: eren-solutions/report-needs

来源:README.md,提交 eac73e7

工具

0
SourceWeft 尚未在沙箱中启动过该软件包,因此其工具未知。

版本历史

1
  1. v0.1.1最新Sep 16, 2026

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