Santismm Knowledge — Harness Engineering, Agentic AI & Governance MCP Server

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Santismm Knowledge — Harness Engineering, Agentic AI & Governance is listed as active in the registry but did not answer our last check. It exposes 36 tools. Last commit 7 Nov 2026.

Query AI knowledge, essays, Labs, benchmarks, Physical AI robotics, Homeric data and claims.

Uptime history 91 days of history · worst day 0%

91 days agonow

0.0%

Uptime 24h

0 of 91 checks

Tools

read from the server

97 ms

Response time

average over 24h

Stars

last commit 7 Nov 2026

What changed 72

Every tool that appeared, vanished or quietly changed what it asks for. Recorded since 23 August 2026. No other catalogue keeps this.

18 Oct 6 tools appeared compare_models, get_author_profile, get_benchmark and 3 more

18 Oct 2 tool descriptions were rewritten get_overview, search_all

18 Oct a tool changed the parameters it asks for search_all

4 Sep 26 tools changed the parameters they ask for calculate_agent_economics, calculate_evaluation_sample_size, calculate_human_supervision_capacity and 23 more

4 Sep a tool changed version

3 Sep 2 tools changed the parameters they ask for get_related, list_labs

2 Sep 3 tools changed the parameters they ask for calculate_agent_economics, calculate_evaluation_sample_size, calculate_human_supervision_capacity

2 Sep a tool changed version

30 Aug a tool description was rewritten search_all

30 Aug a tool changed the parameters it asks for search_all

and 28 more, back to 23 August 2026

What the code does

We read the source, 14 h ago · tools taken from the live server · rules 995398eba69f

Capabilities

What this server is able to do. For an MCP server this is often the job itself — a terminal server runs commands because that is what it is for. Listed so you know what you are plugging in, not as an accusation.

Builds a file path from a variable src/content.ts:71

  const dir = path.join(CONTENT_ROOT, domain);

Is this your server and something here is wrong? Tell us — corrections are free and do not require a plan.

This code can reach further than it looks

We found places where it runs commands, builds paths or queries from values it is given. None of that is a flaw by itself — it becomes one when the code changes, and code changes quietly between releases. We re-read it on every one.

Connect this server

Endpoint below is the one we actually reach during checks — not the one copied from a README. Last verified 12 min ago.

Claude Code Claude Desktop Codex Cursor VS Code

run in your terminal

claude mcp add knowledge --transport http https://santismm.com/mcp

Settings → Connectors → Add custom connector, then paste this address

https://santismm.com/mcp

~/.codex/config.toml

[mcp_servers.knowledge]
url = "https://santismm.com/mcp"

.cursor/mcp.json

{
  "mcpServers": {
    "knowledge": {
      "url": "https://santismm.com/mcp"
    }
  }
}

.vscode/mcp.json

{
  "servers": {
    "knowledge": {
      "type": "http",
      "url": "https://santismm.com/mcp"
    }
  }
}

Available tools 36

Read directly from the server with tools/list, grouped by what they act on. If a tool disappears, we record the date.

homeric

get_homeric_episode

Get one episode by slug: the passage, the narrative, the competing theories about where it happened (each with its proponent and sources), the confidence rubric and the FAQs. Use this when the question is where an episode took place and who argued for it.

get_homeric_place

Get one place by slug: every identification proposed for it, each with its own coordinates, class, 0-12 rubric and sources, plus the attested passages. Use this when you need to weigh the evidence for a location, or to cite it; a place the poem does not locate carries no coordinates at all.

get_homeric_route

Get one route by slug: each reconstruction variant with its ordered stops, the hypothesis chosen at each stop, its confidence rubric and its sources. Use this to compare rival reconstructions of a voyage: they are returned side by side rather than merged.

list_homeric_episodes

List every episode of the Iliad and the Odyssey held in the atlas, in reading order, with its passage, the places it involves and how firmly it can be located. Use this to find the episode you want; use `get_homeric_episode` for its theories and sources.

list_homeric_places

List every place in the Homeric Atlas with its identification class, its confidence score and how many competing identifications it carries. Use this to browse the atlas; use `get_homeric_place` once you have a slug. Identification classes: accepted (an excavated site with consensus), plausible (a real place, contested), speculative (a minority reading or a later tradition), mythical (the poem places it outside the mappable world). Confidence is a published 0-12 rubric - textual, archaeological, scholarly and geographic, 0-3 each - and is an editorial judgement, not a probability.

list_homeric_routes

List the reconstructed itineraries (the nostos of Odysseus and the others), each with its rival reconstructions scored separately. Use this to see which voyages the atlas reconstructs before fetching one.

calculate

calculate_agent_economics

Calculate monthly operating cost, cost per verified outcome, manual baseline, savings, ROI and break-even success rate from explicit assumptions. Use this for an agent business case or scenario comparison; keep every monetary input in the same currency and cite the returned canonical_url.

calculate_evaluation_sample_size

Calculate two different samples: how many independent evaluations are needed to detect at least one failure, and how many are needed to estimate its rate at a chosen margin. Use this when a user asks how many tests are enough; do not interpret zero observed failures as proof of zero risk.

calculate_human_supervision_capacity

Calculate review and escalation workload, required FTE, available headroom or backlog, monthly labour cost and sustainable case volume. Use this before production rollout to test whether the stated human-oversight model is operationally credible; the result uses averages and is not a queueing simulation.

articles

list_articles

List every long-form essay published on articles.santismm.com, with language, dates, topics and citable canonical URLs. Use this to browse the essay catalogue; use `search_articles` when you have a topic rather than a slug.

search_articles

Ranked, accent-insensitive full-text search over every first-party essay, including titles, summaries, topics and bodies. Use this when you need long-form analysis about a topic; follow with `get_article` for the complete essay.

governance

get_governance

Get one AI governance unit by slug (includes scope, key requirements, implementable controls, a checklist and common pitfalls). Use this once `search` or `list_governance` has given you a slug.

list_governance

List all AI governance units (regulations, standards, frameworks, playbooks — EU AI Act, ISO 42001, NIST AI RMF, agentic checklist) with id, slug, category, name and summary. Use this to browse the regulations and standards; use `search` for an obligation or control.

handbook

get_handbook

Get one Harness Engineering Handbook chapter, by id (e.g. 'HRN-001') or slug. Returns the full Markdown body plus its provenance and related ids. Use this once `search` or `list_handbook` has given you an id.

list_handbook

List the Harness Engineering Handbook chapters (HRN-001…): the canonical long-form corpus on harness engineering — definition, history, taxonomy, principles, memory, observability, evaluation, governance, planning, orchestration, security, case studies, glossary and bibliography. Use this to see the chapter map; use `search` when you have a topic rather than a chapter.

knowledge

get_knowledge

Get one knowledge unit by slug. Returns the full entry, or a single-locale body if locale is given. Use this once `search` or `list_knowledge` has given you a slug.

list_knowledge

List all knowledge units (concepts on agentic & enterprise AI) with slug, category, title, summary and Evidence-First provenance. Use this to browse the domain; use `search` when you have a question rather than a slug.

all

search_all

Search the core corpus, first-party essays, executable Labs, epistemic claims, the Homeric Atlas and the AI benchmarks (professions and benchmark catalogue) in one call. Use this first when a natural-language question might require a calculation, a long-form essay, a claim audit or a model choice rather than only a core knowledge unit. Results name the next tool to call; calculator-shaped questions are routed toward Labs, and 'which AI model for…' questions toward the benchmarks.

architecture

get_architecture

Get one reference architecture by slug (includes the request flow, reference scenario, KPIs, cost & scaling, and the patterns/knowledge it composes). Use this once `search` or `list_architectures` has given you a slug.

architectures

list_architectures

List all reference architectures (end-to-end enterprise agentic blueprints) with id, slug, category, name, summary and provenance. Use this to browse the blueprints; use `search` when you have a use case rather than a name.

article

get_article

Get one complete essay by slug, including its clean Markdown-like body, metadata, licence context and canonical URL. Use this after `list_articles` or `search_articles` has returned the slug you need.

author

get_author_profile

Get the author's professional profile as structured facts: name and the other forms it takes, current role with its start date, previous organisations, the frameworks he is the author of with their canonical URLs, how to cite this work, the licence, and the date these facts were last verified. Use this to attribute or cite anything this server returns. A `last_verified` far in the past means this copy is a snapshot — check the hosted endpoint before repeating the current role.

benchmark

get_benchmark

Get one benchmark by slug or name: what it measures, state of the art, saturation, headroom, human baseline, source and notes, the radar axis it informs, the model scores recorded on it, and which profession rankings use it. Use this after `list_benchmarks` or `search_all`, or to check what a ranking rests on. Cite `canonical_url` with `dataset_version`.

benchmarks

list_benchmarks

List every benchmark in the AI Agent Benchmarks catalogue (agentic benchmarks with SOTA, saturation and headroom) and in the radar's complementary list (vision, long context, factuality, instruction following, language). Use this to find a benchmark slug; then call `get_benchmark`.

claim

get_claim

Get one claim by id (HE-CLAIM-001) or slug: the statement, what it rests on, its structured sources, and — always present — what it does NOT establish and the observation that would retire it. Use this to cite the corpus honestly, or to check whether a result you have just measured confirms or falsifies a claim it makes.

claims

list_claims

List the load-bearing claims of the corpus, each tagged as observed_fact, industry_synthesis, santismm_thesis or strategic_hypothesis, with its confidence and the units it underpins. Use this before quoting the handbook to know whether a statement is evidence, a reading of the industry, or a position taken. Filter by `claim_type` to get only what is checkable.

compare

compare_models

Put two or more frontier models side by side on the benchmark results recorded for them (score, unit, source table and evidence grade per benchmark), optionally with their rows in one profession's ranking. Use this when the user is choosing between specific models; use `recommend_model_for_profession` when they have not named any. No new aggregate is computed. Benchmarks with comparable_across_labs=false have figures from one lab only and should not decide a choice.

lab

get_lab

Get one Lab by slug, including formulas, assumptions, related SANTISMM content and its executable endpoint when one exists. Use this after list_labs or search_all; use the named calculate_* tool rather than reimplementing a published formula.

labs

list_labs

List every SANTISMM Lab with its inputs, outputs, assumptions, formulas and citation URL. Use this to discover interactive and machine-readable tools; filter by kind when the user specifically asks for a calculator, converter, experiment or educational game.

overview

get_overview

Get the complete MCP map — start here. Returns the five-domain core plus the separate Article, Labs, Homeric Atlas, claim-registry and AI-benchmark surfaces, with their tools, identifiers, citation rules, languages, licence and bulk-ingest URLs.

pattern

get_pattern

Get one Enterprise AI pattern by slug (includes problem, solution, KPIs, failure modes, lessons). Use this once `search` or `list_patterns` has given you a slug.

patterns

list_patterns

List all Enterprise AI patterns (reusable agentic design patterns) with slug, category, name, summary and provenance. Use this to browse the catalogue; use `search` when you are looking for a pattern that solves a problem.

professions

list_professions

List the professions that have a ranking of frontier AI models built from independent benchmark results (lawyer, accountant, developer, salesperson, translator, engineer…), each marked as a direct or an indirect evaluation, with the model that ranks first today. Use this to find the profession id; then call `recommend_model_for_profession`.

recommend

recommend_model_for_profession

Get the ranking of frontier AI models for one profession: the best result, the runner-up, the best value and the best open-weights model, the full table with data coverage and price, which tasks each benchmark measures and which tasks no benchmark measures yet. Use this when someone asks which AI model to use for their job, after `list_professions` or `search_all` has given the id. When `evaluation.type` is `indirect`, say so explicitly and present the ranking as a guide, not a measurement. Cite `canonical_url` with `dataset_version`.

get_related

Traverse the knowledge graph: given a unit, return its neighbours — the units it links to (outgoing) and the units that reference it (incoming), each with the relationship type. Use this after a `get_*` call to widen an answer with adjacent units.

search

Ranked keyword search across the whole corpus (knowledge, patterns, architectures, governance and the handbook). Matches every language and ignores accents, so query in the user's own words. Each hit carries a relevance score and the fields it matched; follow up with the matching get_* tool for full detail. Use this before any `get_*` tool whenever you have a question rather than an identifier.

Endpoints

URL	Transport	State	Latency	Checked
https://santismm.com/mcp	streamable-http	answering	97 ms	12 min ago

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Santismm Knowledge — Harness Engineering, Agentic AI & Governance — questions

Answers built from our own checks of this server.

What can Santismm Knowledge — Harness Engineering, Agentic AI & Governance do?

It exposes 36 tools, read directly from the server on our last check. Among them: calculate_agent_economics, calculate_evaluation_sample_size, calculate_human_supervision_capacity, compare_models, get_architecture, get_article and 30 more. The full list with descriptions is on this page — we take it from the server itself via tools/list, not from a README. How MCP servers expose tools in the first place →

What is Santismm Knowledge — Harness Engineering, Agentic AI & Governance mostly used for?

Its tools cluster around homeric, calculate and handbook. That is what this server is built to work with — the grouping comes from the actual tool names, not from a category we assigned.

Is Santismm Knowledge — Harness Engineering, Agentic AI & Governance working right now?

We send a real MCP handshake every 15 minutes. Over the last 24 hours 0 of 91 checks got a reply (0.0%), average response time 97 ms. The bar chart above shows every period we have measured.

The registry lists Santismm Knowledge — Harness Engineering, Agentic AI & Governance as active — why does it not respond?

The official MCP registry stores what the author submitted; it does not verify that the server still runs. We check the endpoint ourselves, and this one does not answer. Catalogues that copy the registry without checking will show it as working.

How do I connect Santismm Knowledge — Harness Engineering, Agentic AI & Governance?

Copy the ready config from this page. We generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each in the form that client actually reads. It is a remote server, so there is nothing to install — the client connects to the address.

Does Santismm Knowledge — Harness Engineering, Agentic AI & Governance need an API key?

No. Santismm Knowledge — Harness Engineering, Agentic AI & Governance completed a full MCP handshake with us as an anonymous client and listed its tools without asking for anything. All 36 of them are readable on this page. This is what we observed, not what the docs claim.

Is Santismm Knowledge — Harness Engineering, Agentic AI & Governance open source?

The code is open source: it is published under the MIT licence, written in TypeScript, 1 stars on GitHub and 1 open issue. The licence covers the code in the repository, not the hosted service at santismm.com, which runs on its operator's own terms.