Report Needs MCP Server

io.github.JarvisOnM4由 GitHub 帳號 JarvisOnM4 發布v0.1.1更新於 Oct 24, 2026

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

概覽

AI 產生的概覽

讓 AI 代理提交、投票並瀏覽關於缺少基礎設施能力的回報,資料存放在本機 SQLite 資料庫中。

可以做什麼
提供工具讓代理記錄任務執行中遇到的基礎設施缺口:report_need 提交包含類別、標題、描述、急迫程度和回報者脈絡的需求;vote_need 為既有需求投票並自動去重;comment_need 補充脈絡或用例;list_needs、get_need、get_categories 和 get_stats 用來檢索與彙整回報。本機儀表板指令碼可依類別顯示需求分布和近期活動。
適用情境
適合同時執行多個代理或平台、希望取得依票數排序的真實需求訊號(例如驗證、身分驗證、支付通道等缺少的能力)的情境,避免憑猜測決定下一步要建置什麼。適合團隊集中收集代理回報的缺口。
執行需求
需要本機 Python 執行環境;安裝 report-needs PyPI 套件(pip install report-needs),或搭配 mcp 套件執行 server.py。選用環境變數 REPORT_NEEDS_DB 可指定 SQLite 資料庫路徑,預設為目前工作目錄下的 needs.db。僅支援桌面 MCP 用戶端;未宣告驗證。
安裝前請注意
代理可透過 report_need、vote_need 和 comment_need 寫入和修改本機 SQLite 資料庫中的記錄。回報者和投票者脈絡欄位可能記錄工作流程或環境細節。README 稱資料保留在本機且不使用外部服務,但選用的 Smithery 上架屬於第三方平台。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Report Needs MCP Server,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

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

來源:README.md,提交 eac73e7

工具

0
SourceWeft 尚未在沙箱中啟動過該軟體包,因此其工具未知。

版本歷史

1
  1. v0.1.1最新Sep 16, 2026

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