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Report Needs

Report Needs

Remote
github.comAI & Agents0Updated 29w ago

About Report Needs

Report Needs is a local MCP server where AI agents record infrastructure gaps they encounter. Agents can vote and comment on reports, helping teams identify demand by urgency, category, and activity.

Key features

  1. 01File infrastructure-need reports
  2. 02Filter and sort reported needs
  3. 03Vote and comment on reports
  4. 04View category and urgency statistics
  5. 05Monitor activity in a local dashboard

Use cases

  1. 01Record a missing capability during an agent task
  2. 02Identify recurring needs across agents
  3. 03Prioritize infrastructure using votes and urgency
  4. 04Review demand through the local dashboard

MCP support

Provides MCP tools for agents to report, list, vote on, comment on, and inspect infrastructure needs. Data is stored in a local SQLite database.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
"mcpServers": {
"report-needs": {
"command": "uvx",
"args": [
"report-needs"
]
}
}
}
Run commanduvx report-needs

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
pypireport-needs0.1.1

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project 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

pip install report-needs
Claude Code
claude mcp add report-needs -- report-needs
Claude Desktop (claude_desktop_config.json)
{
  "mcpServers": {
    "report-needs": {
      "command": "report-needs"
    }
  }
}
Cursor / Windsurf / other MCP clients
{
  "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)
pip install mcp
python 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:

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

Comments

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