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io.github.MCFLAMINGO/local-intel

REMOTE · GSB-SWARM-PRODUCTION.UP.RAILWAY.APP · SCANNED AUG 3

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

+2 this week 61 Trust /100
Trust breakdown (6 categories)

How this component scores in each security and reliability category. Every signal is checked automatically against the live server, and we only credit what we can confirm. How we score →

Endpoint Security57
Transport & Reachability100
Schema Quality & AI Usability65
  • AI-judged instruction clarity (good).Pass
  • Context-footprint check failed: tool/resource definitions use about 3672 tokens (~136/item across 27 items; 27 tools + 0 resources), over budget; trim descriptions and params. See how to fix → Fail
  • Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management27
  • Stability observed for 8 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
Tool Coverage100
  • 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
  • 100% of tool parameters carry a description.Pass
Capabilities20
  • Spec-recency check failed: implements MCP spec 2024-11-05; the latest is 2026-07-28. See how to fix → Fail
Install

Add this component to your MCP client. Where a client-specific snippet is available, pick your client below and copy it straight into your config; otherwise use the connection detail shown.

remote · gsb-swarm-production.up.railway.app

# add to Claude Code
claude mcp add --transport http mcflamingo-local-intel https://gsb-swarm-production.up.railway.app/api/local-intel/mcp
# ~/.codex/config.toml
[mcp_servers.mcflamingo-local-intel]
url = "https://gsb-swarm-production.up.railway.app/api/local-intel/mcp"
// opencode.json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "mcflamingo-local-intel": {
      "type": "remote",
      "url": "https://gsb-swarm-production.up.railway.app/api/local-intel/mcp",
      "enabled": true
    }
  }
}
# add to OpenClaw
openclaw mcp add mcflamingo-local-intel --url https://gsb-swarm-production.up.railway.app/api/local-intel/mcp --transport streamable-http
# ~/.hermes/config.yaml
mcp_servers:
  mcflamingo-local-intel:
    url: "https://gsb-swarm-production.up.railway.app/api/local-intel/mcp"
// mcp.json
{
  "mcpServers": {
    "mcflamingo-local-intel": {
      "type": "http",
      "url": "https://gsb-swarm-production.up.railway.app/api/local-intel/mcp"
    }
  }
}

The mcpServers block is a cross-client convention. Remote transports vary, so check your client's docs.

Changelog

Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.

  • 3 Aug 26 +1

    No change was recorded against any check on this day. Stability & Change Management went from 23 to 27. That category is still filling its 30-day observation window: 7 days of observed history at the previous scan, 8 at this one. The score rises as the window fills, whether or not the server changes.

  • 1 Aug 26 +1

    No change was recorded against any check on this day. Stability & Change Management went from 17 to 20. That category is still filling its 30-day observation window: 5 days of observed history at the previous scan, 6 at this one. The score rises as the window fills, whether or not the server changes.

  • 31 Jul 26 −2
    • We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
  • 30 Jul 26 +1
    • We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
  • 28 Jul 26 +1

    No change was recorded against any check on this day. Stability & Change Management went from 3 to 7. That category is still filling its 30-day observation window: 1 days of observed history at the previous scan, 2 at this one. The score rises as the window fills, whether or not the server changes.

  • 27 Jul 26 +1
    • We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
  • 26 Jul 26 58

    First indexed and scored.

Diagnostics

Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.

Captured 3 Aug 2026 · Probed https://gsb-swarm-production.up.railway.app/api/local-intel/mcp

TLS valid

Negotiated TLS 1.3 with TLS_AES_128_GCM_SHA256 .

Subject Issuer Valid from Valid until Key Signature Serial
CN=*.up.railway.app CN=YE1,O=Let's Encrypt,C=US 29 Jul 2026 27 Oct 2026 ECDSA 256 ECDSA-SHA384 6da79bb561da3efeb0e751ca21abd3999fe
SANs: *.up.railway.app, up.railway.app
CN=YE1,O=Let's Encrypt,C=US (CA) CN=Root YE,O=ISRG,C=US 3 Sept 2025 2 Sept 2028 ECDSA 384 ECDSA-SHA384 5ddd70dd31f801c85c186a7a04b80afe
CN=Root YE,O=ISRG,C=US (CA) CN=ISRG Root X2,O=Internet Security Research Group,C=US 13 May 2026 2 Sept 2032 ECDSA 384 ECDSA-SHA384 872165fc34b6e5fba8add5b3705fb53a
CN=ISRG Root X2,O=Internet Security Research Group,C=US (CA) CN=ISRG Root X1,O=Internet Security Research Group,C=US 13 May 2026 2 Sept 2032 ECDSA 384 SHA256-RSA 6c8f1dc727c7117f7baf853ac980f9cd
DNSSEC insecure

Validation of gsb-swarm-production.up.railway.app. Not signed

Zone DS Keys Algorithms Outcome
. trust_anchor 20326, 38696 8, 8 Verified
app. present 23684 8 Verified
railway.app. absent Unsigned (proven) parent-signed NSEC/NSEC3 proves an unsigned delegation
Authentication No authorisation required

The endpoint answered without asking for a token. Anyone who knows the URL can reach it.

Result No authorisation required
HTTP status 200
Transports 3 probes
Transport URL Outcome Status Location
streamable-http https://gsb-swarm-production.up.railway.app/api/local-intel/mcp Verified 200
sse https://gsb-swarm-production.up.railway.app/api/local-intel/mcp Not MCP 200
http (plaintext) http://gsb-swarm-production.up.railway.app/api/local-intel/mcp HTTPS enforced 301 https://gsb-swarm-production.up.railway.app/api/local-intel/mcp
MCP tools — 27 exposed · ~3,467 tokens

The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability.

Tool Tokens
local_intel_ask ~130

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 businesses. Routes internally to the right tools and returns a synthesized, sourced answer with confidence score. Best single entry point for humans and LLMs.

NameTypeReqDescription
questionstringyesPlain English question, e.g. "What restaurant categories are missing in 32082?"
zipstringZIP code (optional — will be extracted from question if present, defaults to 32082)

No output schema declared.

No examples provided.

local_intel_bedrock ~88

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 forecast.'

NameTypeReqDescription
query_contextobjectOptional: { agent_type, agent_id }
zipstringyesZIP code

No output schema declared.

No examples provided.

local_intel_book ~77

Book a specific response to an RFQ — confirms the job with that business. Use after reviewing local_intel_rfq_status responses.

NameTypeReqDescription
notestringOptional note to the business
response_idstringyesUUID of the response to accept
rfq_idstringyesUUID of the RFQ

No output schema declared.

No examples provided.

local_intel_changes ~51

Recently added or owner-verified business listings. Use to detect new openings or data updates.

NameTypeReqDescription
limitintegerMax results (default 20)
zipstringOptional ZIP filter

No output schema declared.

No examples provided.

local_intel_compare ~150

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, franchise expansion, investment screening, and market prioritization.

NameTypeReqDescription
focusstringRanking focus: "opportunity" (default), "hhi", "saturation", "growth", or "population".
limitnumberMax rows to return (default 10).
zipsarrayyesArray of ZIP codes to compare, e.g. ["32082","32081","32084"]. Max 10.

No output schema declared.

No examples provided.

local_intel_complete ~72

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).

NameTypeReqDescription
booking_idstringyesUUID returned by local_intel_book
notestringCompletion note or rating

No output schema declared.

No examples provided.

local_intel_construction ~108

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 business prompts.

NameTypeReqDescription
latnumberLatitude (WGS84) — resolves to nearest FL ZIP
lonnumberLongitude (WGS84)
querystringyesNatural language question about construction market
zipstringZIP code to analyze

No output schema declared.

No examples provided.

local_intel_context ~130

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.

NameTypeReqDescription
latnumberLatitude (WGS84) — resolves to nearest FL ZIP
lonnumberLongitude (WGS84) — required if lat is provided
radius_milesnumberSearch radius in miles (default 1.0)
zipstringAny FL ZIP code

No output schema declared.

No examples provided.

local_intel_corridor ~87

Businesses along a named street corridor. Use for queries like "what is on A1A" or "businesses on Palm Valley Road".

NameTypeReqDescription
limitintegerMax results (default 20)
streetstringyesStreet name (e.g. "A1A", "Palm Valley", "Crosswater")
zipstringOptional ZIP filter

No output schema declared.

No examples provided.

local_intel_decline_response ~99

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.

NameTypeReqDescription
reasonstringOptional reason for declining (e.g. price too high, too far)
response_idstringyesUUID of the response to decline
rfq_idstringyesUUID of the RFQ

No output schema declared.

No examples provided.

local_intel_for_agent ~202

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 first call for any new agent.

NameTypeReqDescription
agent_idstringYour agent UUID for memory + delta computation
agent_typestringreal_estate | financial | ad_placement | logistics | business_owner | civic
budgetnumberAgent budget in pathUSD (optional, for signal prioritization)
depthstringquick (top 5 signals) | full (top 10 + context blocks)
intentstringPlain-language description of what you are trying to decide or do
latnumberLatitude (if no ZIP)
lonnumberLongitude (if no ZIP)
zipstringTarget ZIP code

No output schema declared.

No examples provided.

local_intel_healthcare ~103

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.

NameTypeReqDescription
latnumberLatitude (WGS84) — resolves to nearest FL ZIP
lonnumberLongitude (WGS84)
querystringyesNatural language question about healthcare market
zipstringZIP code to analyze

No output schema declared.

No examples provided.

local_intel_nearby ~108

Find businesses within a radius of any lat/lon point, sorted by distance with compass bearing.

NameTypeReqDescription
categorystringFilter by OSM category
groupstringFilter by semantic group
latnumberyesLatitude of center point
limitintegerMax results (default 15)
lonnumberyesLongitude of center point
radius_milesnumberSearch radius in miles (default 0.5)

No output schema declared.

No examples provided.

local_intel_oracle ~106

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 baked in. No LLM needed — answers derived from population, income, business density, school count, and infrastructure signals.

NameTypeReqDescription
zipstringyesZIP code to analyze (e.g. 32081)

No output schema declared.

No examples provided.

local_intel_project ~202

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 matching verified businesses already operating in that sector. Returns sector gap counts, HHI, population, growth state, and new-build %. Best tool for site selection and franchise expansion when you know the business type but not the ZIP.

NameTypeReqDescription
limitnumberNumber of L1 ZIPs to return (default 5, max 10).
project_typestringyesBusiness type or project category. Examples: restaurant, clinic, banking, construction, real_estate, residential_development, fitness, legal, retail, grocery, auto, beauty, pets.
zipstringOptional. Filter L2 businesses to a specific ZIP. If omitted, returns top ZIPs ranked by score.

No output schema declared.

No examples provided.

local_intel_query ~221

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 restaurant in 32082 that serves lunch" or "Who can do landscaping in Ponte Vedra?" — returns the matching business so your agent can route the order to them. For market intel: "Is 32082 oversaturated with dentists?" ZIP is always required for routing — pass it explicitly or include it in the query.

NameTypeReqDescription
latnumberOptional latitude (WGS84). Resolves to nearest FL ZIP. Use instead of zip for coordinate-based queries.
lonnumberOptional longitude (WGS84). Required if lat is provided.
querystringyesAny plain-English market question. ZIP can be in the query or passed separately.
zipstringOptional ZIP override. If omitted, ZIP is detected from the query or resolved from lat/lon.

No output schema declared.

No examples provided.

local_intel_realtor ~129

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 realtor use-case prompts.

NameTypeReqDescription
latnumberLatitude (WGS84) — resolves to nearest FL ZIP
lonnumberLongitude (WGS84)
querystringyesNatural language question (e.g. "What is the flood risk for this ZIP?", "What commercial gaps exist?")
zipstringZIP code to analyze

No output schema declared.

No examples provided.

local_intel_restaurant ~110

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 prompts.

NameTypeReqDescription
latnumberLatitude (WGS84) — resolves to nearest FL ZIP
lonnumberLongitude (WGS84)
querystringyesNatural language question about restaurant market
zipstringZIP code to analyze

No output schema declared.

No examples provided.

local_intel_retail ~106

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.

NameTypeReqDescription
latnumberLatitude (WGS84) — resolves to nearest FL ZIP
lonnumberLongitude (WGS84)
querystringyesNatural language question about retail market
zipstringZIP code to analyze

No output schema declared.

No examples provided.

local_intel_rfq ~487

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 vague description like "Buy me." Use this when KDS/POS is off or for quote collection. Supports delivery (first-to-accept) and proposal (collect quotes) modes.

NameTypeReqDescription
autonomystringfull=agent books automatically; approve=agent picks best, human confirms; human=human picks from list
budget_usdnumberMax budget in USD (optional)
business_idstringTarget a specific LocalIntel business (required when ordering from a named restaurant)
business_namestringHuman business name, e.g. McFlamingo — shown on the Jobs card
categorystringBusiness category to match, e.g. "restaurant", "food", "delivery", "landscaping", "florist", "handyman", "plumber"
customer_notestringExtra note for the business (allergies, ETA, pickup vs delivery)
deadline_minutesnumberMinutes until deadline (for urgent delivery jobs)
descriptionstringyesFull human-readable request. For food: include items, e.g. "Order for McFlamingo: chicken and broccoli". Do NOT use vague text like "Buy me."
dropoff_addressstringDrop-off address (delivery jobs)
dry_runbooleanIf true, match businesses but do NOT send email/SMS/push/rail notifications. Also auto-enabled for x-agent-id values starting with cursor-test-, test-, agent-test-, or dry-run.
itemsarrayStructured line items, e.g. [{ "name": "chicken and broccoli", "qty": 1 }]
job_typestringdelivery = first-to-accept wins (food orders, pickups); proposal = collect quotes, pick best (services, construction)
notify_emailstringEmail to notify for approve/human autonomy levels
pickup_addressstringPickup address (delivery jobs)
taskstringAlias for description (same meaning)
zipstringZIP code to search businesses in

No output schema declared.

No examples provided.

local_intel_rfq_status ~54

Poll the status of an RFQ. Returns the original request, all responses received so far, and booking details if booked.

NameTypeReqDescription
rfq_idstringyesUUID returned by local_intel_rfq

No output schema declared.

No examples provided.

local_intel_search ~112

Search businesses by name, category, or semantic group (food, retail, health, finance, civic, services).

NameTypeReqDescription
categorystringExact OSM category (restaurant, bank, dentist...)
groupstringSemantic group: food | retail | health | finance | civic | services
limitintegerMax results (default 20, max 50)
querystringText search on name/category/address
zipstringFilter by ZIP code

No output schema declared.

No examples provided.

local_intel_sector_gap ~199

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: NAICS code, sector label, county employment share, demand estimate, confidence tier, and LLM-ready signal narrative. Reads live from Postgres zip_signals — always current. Example: "NAICS 62 Health Care: Jacksonville MSA 136k healthcare employees, ZIP 32082 has no OSM healthcare listings. 28,697 residents, $121k median HHI, retiree index 1.5x. Demand: 7–10 providers." Chain into vertical agents via oracle_vertical. Cost: $0.03 pathUSD.

NameTypeReqDescription
zipstringyesZIP code to analyze (e.g. 32081, 32082, 32259)

No output schema declared.

No examples provided.

local_intel_signal ~102

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.

NameTypeReqDescription
agent_typestringreal_estate | financial | ad_placement | logistics | business_owner | civic
query_contextobjectOptional: { agent_id, purpose }
zipstringyesZIP code

No output schema declared.

No examples provided.

local_intel_stats ~26

Dataset coverage stats: total businesses, confidence scores, query volume, revenue earned.

Input schema present but exposes no named parameters.

No output schema declared.

No examples provided.

local_intel_tide ~118

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.

NameTypeReqDescription
include_layersarrayLayers to include: bedrock, ocean_floor, surface_current, wave_surface (default: all)
query_contextobjectOptional: { agent_type, agent_id, purpose }
zipstringyesZIP code to read tidal state for

No output schema declared.

No examples provided.

local_intel_zone ~90

Spending zone and demographic data for a ZIP code: population, income, home value, rent, ownership rate, zone score. Pass zip or lat/lon.

NameTypeReqDescription
latnumberLatitude (WGS84) — resolves to nearest FL ZIP
lonnumberLongitude (WGS84) — required if lat is provided
zipstringFL ZIP code

No output schema declared.

No examples provided.