Index / MCP servers / io.github.MCFLAMINGO/local-intel

io.github.MCFLAMINGO/local-intel MCP server

io.github.MCFLAMINGO/local-intel is a remote MCP server that gives an AI agent 27 tools, among them local_intel_ask, local_intel_bedrock, local_intel_book. It answers at https://gsb-swarm-production.up.railway.app/api/local-intel/mcp over streamable HTTP, and it listed its tools to an anonymous client, so no sign-in was needed for that. Our probes reached it 6 of 6 times since 11 September 2026; the last check, on 20 October 2026, succeeded.

Status

Answering

Tools

Reliability

6 of 6 checks

Response time

214 ms

Transport

streamable HTTP

Last checked

20 October 2026

Hyperlocal business intelligence for AI agents. 20 MCP tools. Florida-first, Sunbelt expansion.

Description as the publisher wrote it.

The 27 tools io.github.MCFLAMINGO/local-intel offers

Tool	What it does
`local_intel_ask`	Composite NL query layer. Ask any plain-English question about a ZIP — demographics, market opportunity, restaurant gaps, retail saturation, construction activity, investment signals, healthcare, corridor analysis, recent changes, nearby bu Inputs: question, zip
`local_intel_bedrock`	Infrastructure momentum score and active leading indicators for a ZIP from Layer 0. Permits, road projects, flood zones, utility extensions. Predicts conditions 12-36 months ahead. 'Let Google pay for the satellites — we sell the weather fo Inputs: zip, query_context
`local_intel_book`	Book a specific response to an RFQ — confirms the job with that business. Use after reviewing local_intel_rfq_status responses. Inputs: rfq_id, response_id, note
`local_intel_changes`	Recently added or owner-verified business listings. Use to detect new openings or data updates. Inputs: zip, limit
`local_intel_compare`	Compare up to 10 ZIP codes side-by-side and get a ranked opportunity table. Returns per-ZIP signals (HHI, capture rate, infra momentum, consumer profile, top gap) plus a top_pick recommendation with reasoning. Best tool for site selection, Inputs: zips, focus, limit
`local_intel_complete`	Mark a booked job as complete and settle payment to the local merchant wallet (Tempo pathUSD when SETTLEMENT_ENABLED=true; otherwise records settled_intent and feeds the forecast loop). Inputs: booking_id, note
`local_intel_construction`	Construction and home services market intelligence for a ZIP. Ask about contractor density, active permits, housing starts, population growth driving demand. Returns structured data with confidence score. Trained on 100 construction busines Inputs: query, zip, lat, lon
`local_intel_context`	Full spatial context block for any FL zip or lat/lon. Returns anchor business, nearby businesses in distance rings, zone intelligence, and category breakdown. Best first call for any location query. Covers all 1,473 FL ZIPs via fl_zip_geo. Inputs: zip, lat, lon, radius_miles
`local_intel_corridor`	Businesses along a named street corridor. Use for queries like "what is on A1A" or "businesses on Palm Valley Road". Inputs: street, zip, limit
`local_intel_decline_response`	Decline a specific response to an RFQ and get the next in queue. Use when a client rejects the first responder — returns the next pending response automatically. First come first served queue. Inputs: rfq_id, response_id, reason
`local_intel_for_agent`	PREMIUM composite entry point ($0.05). Declare your agent_type and intent, receive pre-ranked top-10 signals assembled from all 4 data layers, personalized for your use case. Includes delta since your last query if agent_id provided. Best f Inputs: agent_type, intent, zip, lat, lon, budget
`local_intel_healthcare`	Healthcare market intelligence for a ZIP. Ask about provider density, patient demographics, demand gaps, senior population. Returns structured data with confidence score. Trained on 100 healthcare business prompts. Inputs: query, zip, lat, lon
`local_intel_nearby`	Find businesses within a radius of any lat/lon point, sorted by distance with compass bearing. Inputs: lat, lon, radius_miles, category, group, limit
`local_intel_oracle`	Pre-baked economic oracle for a ZIP. Returns: restaurant saturation (is there room for another?), price-tier gap analysis (what menu price is missing?), growth trajectory (growing/empty-nest/stable), and 3 pre-formed questions with answers Inputs: zip
`local_intel_project`	Project-type intelligence: pass a project_type (restaurant, clinic, banking, construction, real_estate, residential_development, fitness, legal, retail, auto, etc.) and get L1 ZIPs ranked by market or residential opportunity score plus L2 m Inputs: project_type, zip, limit
`local_intel_query`	START HERE. Natural language entry point for both market intelligence AND business routing. Ask about a market, find a business, or route a customer request. Auto-detects ZIP, industry vertical, and intent. For customer agents: "Find a rest Inputs: query, zip, lat, lon
`local_intel_realtor`	Real estate intelligence for a ZIP. Ask natural-language questions: demographics, commercial gaps, flood risk, school proximity, infrastructure signals, market saturation. Returns structured data with confidence score. Trained on 100 realto Inputs: query, zip, lat, lon
`local_intel_restaurant`	Restaurant and food service market intelligence for a ZIP. Ask about saturation scores, price-tier gaps, capture rates, corridor analysis, tidal momentum. Returns structured data with confidence score. Trained on 100 restaurant business pro Inputs: query, zip, lat, lon
`local_intel_retail`	Retail market intelligence for a ZIP. Ask about store categories, spending capture rates, consumer profile, undersupplied niches. Returns structured data with confidence score. Trained on 100 retail business prompts. Inputs: query, zip, lat, lon
`local_intel_rfq`	Route a customer request to local businesses — food orders, delivery, services, or any job. ALWAYS include the full order or ask in description (or items[]), plus business_id/business_name when ordering from a specific place. Never send a v Inputs: job_type, category, zip, description, task, items
`local_intel_rfq_status`	Poll the status of an RFQ. Returns the original request, all responses received so far, and booking details if booked. Inputs: rfq_id
`local_intel_search`	Search businesses by name, category, or semantic group (food, retail, health, finance, civic, services). Inputs: zip, query, category, group, limit
`local_intel_sector_gap`	Ranked sector gap analysis for a ZIP. Identifies NAICS sectors present at county level (CBP/CES employment) but underrepresented at ZIP (OSM business counts) — the structural whitespace in a local economy. Returns ranked opportunities with: Inputs: zip
`local_intel_signal`	Investment and activity signal for a ZIP. Composite score 0-100 with band (strong_buy/accumulate/hold/reduce/avoid), top reasons, and avoid flags. Best for real estate and financial agents. Inputs: zip, agent_type, query_context
`local_intel_stats`	Dataset coverage stats: total businesses, confidence scores, query volume, revenue earned.
`local_intel_tide`	Tidal reading for a ZIP — temperature (0-100), direction (surging/heating/stable/cooling/receding), seasonal context. Synthesizes all 4 data layers. Best for agents deciding WHERE to act next. Inputs: zip, include_layers, query_context
`local_intel_zone`	Spending zone and demographic data for a ZIP code: population, income, home value, rent, ownership rate, zone score. Pass zip or lat/lon. Inputs: zip, lat, lon

Add io.github.MCFLAMINGO/local-intel to your AI client

Every block below points at https://gsb-swarm-production.up.railway.app/api/local-intel/mcp. Pick your client and copy.

Claude Code: one command in your terminal

claude mcp add --transport http io-github-mcflamingo-local-intel https://gsb-swarm-production.up.railway.app/api/local-intel/mcp

Claude Desktop: claude_desktop_config.json

{
  "mcpServers": {
    "io-github-mcflamingo-local-intel": {
      "command": "npx",
      "args": ["-y", "mcp-remote", "https://gsb-swarm-production.up.railway.app/api/local-intel/mcp"]
    }
  }
}

Cursor: ~/.cursor/mcp.json, or .cursor/mcp.json in a project

{
  "mcpServers": {
    "io-github-mcflamingo-local-intel": {
      "url": "https://gsb-swarm-production.up.railway.app/api/local-intel/mcp"
    }
  }
}

VS Code and GitHub Copilot: .vscode/mcp.json

{
  "servers": {
    "io-github-mcflamingo-local-intel": {
      "type": "http",
      "url": "https://gsb-swarm-production.up.railway.app/api/local-intel/mcp"
    }
  }
}

Zed: Zed settings.json

{
  "context_servers": {
    "io-github-mcflamingo-local-intel": {
      "url": "https://gsb-swarm-production.up.railway.app/api/local-intel/mcp"
    }
  }
}

Windsurf: ~/.codeium/mcp_config.json

{
  "mcpServers": {
    "io-github-mcflamingo-local-intel": {
      "serverUrl": "https://gsb-swarm-production.up.railway.app/api/local-intel/mcp"
    }
  }
}

JetBrains AI Assistant: Settings, Tools, AI Assistant, MCP, New MCP Server, as JSON

{
  "mcpServers": {
    "io-github-mcflamingo-local-intel": {
      "url": "https://gsb-swarm-production.up.railway.app/api/local-intel/mcp"
    }
  }
}

Continue: .continue/mcpServers/neuronto.yaml

name: io.github.MCFLAMINGO/local-intel
version: 0.0.1
schema: v1
mcpServers:
  - name: io.github.MCFLAMINGO/local-intel
    type: streamable-http
    url: https://gsb-swarm-production.up.railway.app/api/local-intel/mcp

Gemini CLI: ~/.gemini/settings.json

{
  "mcpServers": {
    "io-github-mcflamingo-local-intel": {
      "httpUrl": "https://gsb-swarm-production.up.railway.app/api/local-intel/mcp"
    }
  }
}

Codex CLI: MCP server config

{
  "mcpServers": {
    "io-github-mcflamingo-local-intel": {
      "type": "http",
      "url": "https://gsb-swarm-production.up.railway.app/api/local-intel/mcp"
    }
  }
}

Warp: MCP servers, + Add, paste JSON

{
  "mcpServers": {
    "io-github-mcflamingo-local-intel": {
      "url": "https://gsb-swarm-production.up.railway.app/api/local-intel/mcp"
    }
  }
}

Goose: a one-click extension link

goose://extension?url=https%3A%2F%2Fgsb-swarm-production.up.railway.app%2Fapi%2Flocal-intel%2Fmcp&type=streamable_http&id=io-github-mcflamingo-local-intel&name=io.github.MCFLAMINGO/local-intel

Is io.github.MCFLAMINGO/local-intel up right now?

It answered our last check on 20 October 2026 in 214 ms. Over 6 checks since 11 September 2026 it answered 6. Status here comes from Neuronto's own probes, not from the publisher.

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Bizintel8 tools AdvocateMCP15 tools Bezal — Local Business Intelligence for AI Agents13 tools Google Maps (Mapstools)5 tools Moonlings — Local Business Intelligence8 tools Nose for Leads11 tools

Questions about io.github.MCFLAMINGO/local-intel

How many tools does io.github.MCFLAMINGO/local-intel have?

27, as returned by the server's own tools/list on 12 September 2026: local_intel_ask, local_intel_bedrock, local_intel_book, local_intel_changes, local_intel_compare, local_intel_complete, local_intel_construction, local_intel_context, and 19 more.

Is io.github.MCFLAMINGO/local-intel down?

It answered our last check on 20 October 2026 in 214 ms. Over 6 checks since 11 September 2026 it answered 6.

How do I add io.github.MCFLAMINGO/local-intel to Cursor?

Put the server under mcpServers in ~/.cursor/mcp.json with the URL https://gsb-swarm-production.up.railway.app/api/local-intel/mcp. The exact JSON is above, with the same setup for Claude Code, Claude Desktop, VS Code, Windsurf, Zed, Gemini CLI and the rest.

Does io.github.MCFLAMINGO/local-intel need an API key?

It listed its tools to an anonymous client, so reading the tool list needs no key. Individual tools can still ask for credentials in their own inputs.

Where this comes from

Publisher: io.github.mcflamingo. Endpoint host: gsb-swarm-production.up.railway.app. ARD identifier: urn:air:io.github.mcflamingo:mcp:local-intel. First indexed 10 September 2026. The tools are exactly what the server returned; nothing on this page is inferred from its name. Ranking in Neuronto search is never for sale.

Is this your server? Get a message the day it stops answering or its tools change: monitoring, 14 days free. Or claim the domain to manage how it is listed.