OpenSEO
Keyword research, site audits, rank tracking and AI visibility for your AI agent.
Query AI knowledge, essays, Labs, benchmarks, Physical AI robotics, Homeric data and claims.
Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.
4/4 Prüfungen bestanden · Was du fragst, läuft über den Server des Anbieters (santismm.com) · ✓ Befehle geprüft am 13. Nov. 2026
Zuerst: Welche KI nutzt du?
Wähle deine App, dann erscheinen die Schritte unten.
Klappt mit Claude · etwa 2 Min.
Kein Schlüssel, nichts zu installieren · Einmal auf claude.ai oder in der Desktop-App einrichten, dann im Chat nutzen · kostenlose Konten können 1 hinzufügen · bei Team/Enterprise fügt ein Owner ihn hinzu
CustomizeConnectors
Kopiere jeden Wert in das gleichnamige Feld in Claude und klicke Continue
Santismm Knowledge — Harness Engineering, Agentic AI & Governancehttps://santismm.com/mcpKlicke auf der von Claude erkannten Anmelde-Seite auf Continue · wähle bei Authentication, was der Anbieter angibt (Sign in now, Sign in when needed oder No sign in), dann Add
+ConnectorsSantismm Knowledge — Harness Engineering, Agentic AI & Governance
Nutze Santismm Knowledge — Harness Engineering, Agentic AI & Governance und sag mir, was du für mich tun kannst; zeig mir dann eine Sache✓ Wenn Claude sagt, dass es Santismm Knowledge — Harness Engineering, Agentic AI & Governance nutzt, oder ein Werkzeug von Santismm Knowledge — Harness Engineering, Agentic AI & Governance in der Antwort zeigt, bist du verbunden
Menünamen am 11. Nov. 2026 mit der Hilfe von Anthropic abgeglichen · dein Bildschirm kann je nach App-Version leicht abweichen
Klappt mit ChatGPT je nach Tarif
Volles MCP: ChatGPT Business, Enterprise oder Edu im Web · Pro: verbindet mit Lese-/Abrufrechten, Werkzeuge, die Daten ändern, gehen evtl. nicht · Plus: in der Doku nicht bestätigt; siehst du auf der Plugins-Seite eine Option für eigene MCP-Server, kannst du es versuchen · nur Web
Plugins+Add custom MCP server
Namen eingeben, Adresse unter Connection einfügen, Risikohinweis abhaken und Create as a plugin klicken
Santismm Knowledge — Harness Engineering, Agentic AI & Governancehttps://santismm.com/mcpNeuen Chat öffnen und vor dem Tippen Santismm Knowledge — Harness Engineering, Agentic AI & Governance aus deinen Plugins wählen
Nutze Santismm Knowledge — Harness Engineering, Agentic AI & Governance und sag mir, was du für mich tun kannst; zeig mir dann eine Sache✓ Wenn ChatGPT sagt, dass es Santismm Knowledge — Harness Engineering, Agentic AI & Governance nutzt, oder ein Werkzeug von Santismm Knowledge — Harness Engineering, Agentic AI & Governance in der Antwort zeigt, bist du verbunden
Menünamen am 11. Nov. 2026 mit der Hilfe von OpenAI abgeglichen · dein Bildschirm kann je nach App-Version leicht abweichen
Klappt mit Claude Code · etwa 2 Min.
Kein Schlüssel, nichts zu installieren
Mac: Command+Leertaste drücken und Terminal tippen · Windows: PowerShell öffnen
claude mcp add --transport http --scope user knowledge https://santismm.com/mcpSantismm Knowledge — Harness Engineering, Agentic AI & Governance sollte in der Liste als verbunden erscheinen
Nutze Santismm Knowledge — Harness Engineering, Agentic AI & Governance und sag mir, was du für mich tun kannst; zeig mir dann eine Sache✓ Wenn Claude Code sagt, dass es Santismm Knowledge — Harness Engineering, Agentic AI & Governance nutzt, oder ein Werkzeug von Santismm Knowledge — Harness Engineering, Agentic AI & Governance in der Antwort zeigt, bist du verbunden
Menünamen am 11. Nov. 2026 mit der Hilfe von Anthropic abgeglichen · dein Bildschirm kann je nach App-Version leicht abweichen
Klappt mit Cursor · etwa 2 Min.
Kein Schlüssel, nichts zu installieren
Nutze Santismm Knowledge — Harness Engineering, Agentic AI & Governance und sag mir, was du für mich tun kannst; zeig mir dann eine Sache✓ Wenn Cursor sagt, dass es Santismm Knowledge — Harness Engineering, Agentic AI & Governance nutzt, oder ein Werkzeug von Santismm Knowledge — Harness Engineering, Agentic AI & Governance in der Antwort zeigt, bist du verbunden
Menünamen am 11. Nov. 2026 mit der Hilfe von Cursor abgeglichen · dein Bildschirm kann je nach App-Version leicht abweichen
Klappt mit VS Code · etwa 2 Min.
Kein Schlüssel, nichts zu installieren
VS Code fragt nach einer Bestätigung; klicke Install
Nutze Santismm Knowledge — Harness Engineering, Agentic AI & Governance und sag mir, was du für mich tun kannst; zeig mir dann eine Sache✓ Wenn VS Code sagt, dass es Santismm Knowledge — Harness Engineering, Agentic AI & Governance nutzt, oder ein Werkzeug von Santismm Knowledge — Harness Engineering, Agentic AI & Governance in der Antwort zeigt, bist du verbunden
Menünamen am 11. Nov. 2026 mit der Hilfe von VS Code abgeglichen · dein Bildschirm kann je nach App-Version leicht abweichen
Andere Apps mit MCP, etwa Windsurf, Zed oder Gemini CLI, fügen Server unterschiedlich hinzu. Sieh in der App-Liste nach
Adresse für Apps, die über das Web verbinden
https://santismm.com/mcpJSON-Einstellungen stehen unten unter „Für Entwickler“
Claude Code
claude mcp add --transport http --scope user knowledge https://santismm.com/mcpCursor (~/.cursor/mcp.json)
{
"mcpServers": {
"knowledge": {
"url": "https://santismm.com/mcp"
}
}
}VS Code (mcp.json)
{
"servers": {
"knowledge": {
"type": "http",
"url": "https://santismm.com/mcp"
}
}
}Diese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.
Basierend darauf, wie sich dieser Server verbindet, und auf der eigenen Doku jeder App, geprüft am 10. Nov. 2026.
Verbinden sich über das Internet in
ClaudeChatGPTGooseLM StudioMsty StudioCherry StudioCursorVS Code + GitHub CopilotVisual StudioWindsurf (Devin Desktop)ZedKiroClineContinueJetBrains AI AssistantClaude CodeCodex CLIGemini CLIOpenCodenodecodeWarpLibreChatOpen WebUIRaycast
Tool-Namen und -Beschreibungen genau so, wie der Server sie am 13. Nov. 2026 gemeldet hat. Geschrieben hat sie der Entwickler, nicht wir; wir zeigen sie als reinen Text.
get_author_profileGet 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
get_overviewGet the complete MCP map — start here. Returns the five-domain core plus the separate Article, Labs, Homeric Atlas, claim-registry, AI-benchmark and Physical AI surfaces, with their tools, identifiers, citation rules, languages, licence and bulk-ingest URLs. Federated surfaces th
search_allSearch the core corpus, first-party essays, executable Labs, epistemic claims, the Homeric Atlas, the AI benchmarks (professions and benchmark catalogue) and Physical AI (robot platforms, documented deployments, deployment guide) in one call. Use this first when a natural-languag
list_knowledgeList 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.
get_knowledgeGet 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_patternsList 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.
get_patternGet 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.
list_architecturesList 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.
get_architectureGet 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.
list_governanceList 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.
get_governanceGet 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_handbookList 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.
get_handbookGet 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.
searchRanked 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
list_articlesList 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.
get_articleGet 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.
search_articlesRanked, 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.
list_professionsList 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
recommend_model_for_professionGet 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 some
compare_modelsPut 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
list_benchmarksList 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
get_benchmarkGet 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
list_labsList 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.
get_labGet 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.
calculate_agent_economicsCalculate 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 canon
calculate_evaluation_sample_sizeCalculate 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 z
calculate_human_supervision_capacityCalculate 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 n
search_physical_aiSearch the Physical AI dataset — real robot platforms (humanoids, quadrupeds, mobile manipulators, UGVs, drones), documented deployments with sources, the enterprise deployment guide, the autonomy taxonomy and the evidence methodology. Filter by type and taxonomy ids. Each result
get_physical_ai_itemRead one record by type and slug: a platform sheet (specs with test conditions, provenance and sources, autonomy by task, evidence stage, access, lifecycle), a documented case study (sourced facts, published KPIs, lessons), a guide, a cited source by id — or, with type 'source' a
compare_physical_ai_platformsCompare 2–5 platforms side by side on published fields only — payload, runtime, weight, speed, IP rating, temperature range, price, autonomy, coordination, control, perception, environments, sectors, evidence stage, access and lifecycle. Every cell says whether the value is publi
calculate_physical_ai_roiRun the Physical AI calculator's own 36-month model: manual vs robotic TCO, annual savings, upfront investment, payback month, ROI, coverage, supervision and incidents, plus payback sensitivity to hourly cost, capex, coverage, integration, maintenance and uptime. Every input is o
assess_physical_ai_fitRun the deployment guide's readiness assessment: score per area and overall, the band and its guidance, the weakest area, blockers (items answered 'no') and the questions still unanswered, plus the platforms and documented deployments that match the environment, sector and family
get_relatedTraverse 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.
list_homeric_placesList 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 consen
get_homeric_placeGet 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 coordina
list_homeric_episodesList 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.
get_homeric_episodeGet 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.
list_homeric_routesList 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.
get_homeric_routeGet 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_claimsList 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 in
get_claimGet 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 measur
Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 16. Nov. 2026
Der Registry-Name wurde über die Domain santismm.com bestätigt (die Registry prüft, wem die Domain gehört)
Code zuletzt geändert: vor 9 Tagen
Nicht relevant: Cloud-Server des Inhabers von santismm.com; du führst keinen Code aus dem Repo aus
Antwort in 315 ms (HTTP 200)
Keine Anmeldung nötig
Wir haben 41 Tool-Beschreibungen gelesen und keine versteckten Anweisungen an die KI gefunden
Fragen, Tipps teilen oder melden, dass etwas nicht geht. Sortiert nach „hilfreich“.
Noch keine Beiträge. Stell die erste Frage oder teile einen Tipp.
Beiträge hier stammen von Nutzern, nicht vom PopNx-Team.
Noch keine Bewertungen
Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.
Er hat 4 von 4 zutreffenden Basischecks bestanden. Den Code haben wir nicht gelesen. Bevor du einen Schlüssel oder Token hinzufügst, sieh nach, welche Zugriffe der Server verlangt, und nutze einen Schlüssel, der nur die Berechtigungen hat, die du brauchst.
Die Registry nennt keinen erforderlichen Schlüssel, manche Server bitten dich aber bei der ersten Nutzung, dich anzumelden.
Er läuft in der Cloud des Entwicklers. Du verbindest dich übers Internet, ohne etwas zu installieren, aber was du sendest, läuft über die Server des Entwicklers.
Das GitHub-Repo wurde zuletzt vor 9 Tagen geändert, und die neueste Version (0.6.1) kam vor 9 Tagen in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Er verbindet sich per URL und funktioniert daher auch in Apps mit Remote-MCP, etwa ChatGPT im Web (volles MCP ab Business; Pro nur lesend).
In derselben Kategorie: OpenSEO, Exa, Mockserver, Microsoft Learn MCP, Docs
Gleiche Kategorie, andere Entwickler, Befehle bereits geprüft. Offizielle zuerst, dann nach Sternen.
So liest du eine Karte:↓ Downloads pro Wochei★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti
Keyword research, site audits, rank tracking and AI visibility for your AI agent.
Connect AI agents to Exa for web search, content fetching, and multi-step research.
Mock, record/replay, verify and chaos-test any HTTP, REST, gRPC or LLM dependency over MCP.
Official Microsoft Learn MCP Server – real-time, trusted docs & code samples for AI and LLMs.
Search and read Empryo's documentation. Read-only, no auth, no local access.
Unverändert aus dem Repo des Entwicklers übernommen. PopNx MCP hat den Inhalt weder geprüft noch empfiehlt es ihn. HTML, Bilder und Skripte wurden entfernt. Links führen von dieser Website weg.
MCP server for the Santismm Knowledge Platform — five core knowledge domains,
first-party essays, Homeric Atlas datasets and epistemic claims.
This repository is generated from the platform at santismm.com. Do not edit it by hand; changes are overwritten on the next sync. Corrections go through the site.
The same server is hosted, so most people want the endpoint rather than this repository:
{ "mcpServers": { "santismm-knowledge": { "type": "http", "url": "https://santismm.com/mcp" } } }
Docs: https://santismm.com/en/mcp · Registry: com.santismm/knowledge
Derived from the same list the site renders on its own MCP page, so a registry added there is linked from here too — and a directory that checks for a backlink before ranking a server finds one without anybody remembering to add it.
npm ci && npm run build && npm start
The core corpus ships in content/ and is read from disk, so its tools work offline. The federated Article, Labs and benchmark tools read their canonical first-party APIs over HTTPS (benchmarks: SANTISMM_BENCHMARKS_URL). Point the core corpus elsewhere with SANTISMM_CONTENT_DIR.
npx santismm-knowledge-mcp
Or in an MCP client config (stdio):
{ "mcpServers": { "santismm-knowledge": { "command": "npx", "args": ["santismm-knowledge-mcp"] } } }
The npm package carries the corpus frozen at publish time; this repository and the hosted endpoint update continuously. When freshness matters, prefer the endpoint.
uvx santismm-knowledge-mcp
The Python package (in python/) is a zero-dependency stdio proxy to the hosted endpoint — it ships no corpus, so it is always fresh.
{ "mcpServers": { "santismm-knowledge": { "command": "uvx", "args": ["santismm-knowledge-mcp"] } } }
Code is MIT (LICENSE); the knowledge corpus in content/ is CC BY 4.0 (content/LICENSE) — two licences because CC BY is not a software licence and MIT is not a content licence.
41 read-only tools over knowledge, patterns, architectures, governance, the Harness Engineering Handbook, first-party Articles, Labs and the AI benchmarks, each declaring an outputSchema and returning validated structuredContent. Every tool is annotated readOnlyHint: true, destructiveHint: false and idempotentHint: true. The federated Article, Labs and benchmark tools declare openWorldHint: true; local-corpus tools remain false.
Content in seven languages (en/es/pt/fr/de/ja/zh).
Code: MIT. Content: Content © Santiago Santa María Morales, licensed CC BY 4.0. Attribution required: credit the author and link the canonical URL. (CC-BY-4.0, https://creativecommons.org/licenses/by/4.0/).