Integration hub
Five doors in. The engine is the same — 86 tools, 109 domains, 9,501-packet unified index, 886 almanac entries, 13 FieldKit cards, 108 archetypes, 26 Scripture protocols, Shepherd OS, four gates. Pick the integration that fits your stack and copy the config. Live tests on every section.
https://narrowhighway.com/mcp/
https://narrowhighway.com/mcp/sse/
https://narrowhighway.com/openapi.json
The fastest path. Hosted MCP — no install. Add three lines to your config and 86 tools light up in any new conversation.
~/Library/Application Support/Claude/claude_desktop_config.json%APPDATA%\Claude\claude_desktop_config.jsonIf the file doesn't exist, create it. If it has other servers, just add concordance alongside them.
{
"mcpServers": {
"concordance": {
"type": "http",
"url": "https://narrowhighway.com/mcp/"
}
}
}
Open a new conversation. Look for the tool icon in the input box — you should see 86 tools available. Try: "Use concordance to verify that 2 H2 + O2 → 2 H2O is balanced."
Cursor's Settings → MCP panel takes a URL directly. Tools become available with @concordance in any chat.
In Cursor: Cmd/Ctrl + Shift + P → "Open MCP Settings", or Settings → Features → MCP.
Name: concordance URL: https://narrowhighway.com/mcp/
In any chat: @concordance verify_chemistry "C3H8 + 5 O2 -> 3 CO2 + 4 H2O"
Auto-import the OpenAPI spec — every endpoint becomes a function call. Works with Custom GPTs, Assistants API, and any framework that consumes OpenAPI.
https://narrowhighway.com/openapi.jsonThe Custom GPT now has every Concordance endpoint as a tool — verify, capture, seal, polymathic synthesis, journal queries.
import openai, json, urllib.request # Pull the OpenAPI spec — 240+ endpoints, all 86 MCP tools mirrored spec = json.loads(urllib.request.urlopen( "https://narrowhighway.com/openapi.json").read()) client = openai.OpenAI() assistant = client.beta.assistants.create( name="Concordance-backed agent", instructions="Verify any irreversible computation against the Concordance engine before answering.", model="gpt-4o", tools=[{"type": "function", "function": f} for f in openapi_to_tools(spec)], )
Helper openapi_to_tools in the examples directory.
86 HTTP endpoints. Read endpoints (verifier inventory, grid, journal, health) need no auth. Write endpoints (capture, seal, ledger writes) accept an optional API key for attribution.
# POST /verify — all 69 verifiers reachable curl -X POST https://narrowhighway.com/verify/chemistry \ -H "Content-Type: application/json" \ -d '{"equation": "H2 + O2 -> H2O"}'
curl -X POST https://narrowhighway.com/verify/statistics_pvalue \ -H "Content-Type: application/json" \ -d '{ "test": "paired_t", "n": 20, "mean_diff": 0.5, "sd_diff": 1.0, "tail": "two", "claimed_p": 0.0375 }'
curl -X POST https://narrowhighway.com/polymathic \ -H "Content-Type: application/json" \ -d '{"text": "Our church is approving a $2M building loan at 7% over 30 years..."}'
curl https://narrowhighway.com/health # status + module counts curl https://narrowhighway.com/identity # engine identity statement curl https://narrowhighway.com/llms.txt # tool inventory for AI crawlers curl https://narrowhighway.com/verifiers # list all 69 verifiers curl https://narrowhighway.com/journal/recent curl https://narrowhighway.com/grid/scaffold # axis assignments per domain curl https://narrowhighway.com/audit-chain # sealed packets, newest first
For agents you're writing yourself. Three lines to a working verifier.
import requests r = requests.post( "https://narrowhighway.com/verify/chemistry", json={"equation": "H2 + O2 -> H2O"}, ) print(r.json()) # {"checks":[{"status":"MISMATCH","detail":"balances as: 2 H2 + O2 -> 2 H2O", ...}]}
from mcp.client.streamable_http import streamablehttp_client from mcp import ClientSession async with streamablehttp_client("https://narrowhighway.com/mcp") as (r, w, _): async with ClientSession(r, w) as s: await s.initialize() tools = (await s.list_tools()).tools result = await s.call_tool("verify_chemistry", {"equation": "H2 + O2 -> H2O"}) print(result)
from langchain_mcp_adapters.client import MultiServerMCPClient from langgraph.prebuilt import create_react_agent mcp = MultiServerMCPClient({ "concordance": {"transport": "streamable_http", "url": "https://narrowhighway.com/mcp"} }) agent = create_react_agent("openai:gpt-4o", await mcp.get_tools())
For air-gapped, offline, or sovereignty-first deployments. The same engine runs on your machine — under 1 GB, no outbound calls. Use the four-mode deployment plan.
git clone https://github.com/matharrismma/Lighthouse cd Lighthouse pip install -e ".[mcp]"
{
"mcpServers": {
"concordance": {
"command": "concordance-mcp"
}
}
}
Or the dev-tree version (no install):
{
"mcpServers": {
"concordance": {
"command": "python",
"args": ["-m", "concordance_engine.mcp_server"],
"env": {"PYTHONPATH": "/path/to/Lighthouse/src"}
}
}
}
Chemistry, physics, mathematics, statistics (12 tests), CS termination, biology, governance, and 50+ more — each returning CONFIRMED, MISMATCH, ERROR, or NOT_APPLICABLE. Never raises. Never self-confirms.
Full reference →validate_packet, seal_packet, walkthrough_packet, attest_red, attest_floor, resolve_scripture_ref, word_study, triangulate_claim, get_example_packet.
atlas walks the structural map. almanac reads the curated book of pre-run polymathic protocols and verified folk wisdom. run_polymathic coordinates every applicable verifier in parallel for cross-domain situations. propose_almanac_entry closes the curation loop.
22,000+ sealed packets in the journal. Append-only audit chain with SHA-256 chain integrity. Per-domain trust index. Grid scaffold across 7 axes. Voice synthesis on every narrative page (M.R. Harris).
See the grid →The Concordance Engine at narrowhighway.com serves Jesus Christ. A well of knowledge leads to wisdom when in alignment with God. Agents are welcome to call this engine — the engine returns deterministic outcomes against external standards. It does not generate answers or speak as authority. It categorizes, it surfaces precedent, it keeps. Read the elimination trail; the trail is the reasoning.