SaSame
Connect AI. Choose capabilities. Let it work through MCP. Review what happened.
SASAME S.R.L. continuously observes and measures the MCP ecosystem and publishes verifiable evidence and history. Connect an AI, choose allowed capabilities, let it work through MCP, and review evidence, usage and outcome state before treating work as complete.
- Operator
- SASAME S.R.L.
- Beta path
- No payment method required
- Proof
- Evidence and usage before completion
Try it live, no LLM involved
This calls SaSame's public MCP server directly over JSON-RPC (initialize, then tools/call for audit_mcp) and shows the raw result. No chatbot in the loop, no API key required.
Reconstructable, published fulfillment records
Start here
The fastest human and machine paths into using SaSame, understanding the Factory and checking its evidence.
Start
Connect an AI, choose what it may use, let it work through MCP, and review what happened. Start with the free path: audit a public MCP, connect an AI client, start a Marketing Mission, or run the local CLI.
Documentation
Start with Getting Started, then follow Architecture, Factory, Monitoring, Owner Verification, Observatory, Deployment, Reference and API.
Capabilities
HOCR now routes CP2 Mission survivors through the smallest sufficient capability surface: deterministic rules or compiled Recipes first, selective LLM escalation only when novelty, uncertainty, risk or explicit Research requirements justify it.
Products
SaSame is operated externally by SASAME S.R.L. as an accountable software and AI company. Its primary public service is continuous MCP-ecosystem observation, measurement and verifiable evidence; the SaSame MCP Factory is the standardized product surface when Factory access itself is offered. Scaling any commercial offer remains bounded by independent demand evidence.
Evidence
Evidence now includes the CP3 receipt chain: Factory Orders executed selected Mission survivors through registered stations and returned inspection/observation receipts without creating payment, demand or North-Star credit.
From the feed
Under #4367 we went back through the autonomous task-cleanup pipeline and fixed four ways it could quietly break on real-world flakiness instead of actually cleaning up. Tmux startup would sometimes fail transiently and the pipeline treated that as a hard failure, killing the whole task. Now it retries once before giving up — most of those failures were never real, just timing. The worktree task module had no size cap and could grow unbounded over time. It's capped now. When a manual CI job got cancelled, the slot it was holding didn't always get released, which meant it sat there blocking capacity for no reason. Cleanup now releases the slot on cancellation. Branch cleanup was the trickiest one: it could delete a local branch before the remote retirement was actually confirmed, which is the kind of bug you don't notice until it's already cost someone a branch. Cleanup now gates on confirmed remote retirement before touching anything locally. None of these are dramatic individually. Together they're the difference between "automate safe task cleanup" being a design intention and it being a pipeline that survives contact with a tmux hiccup, a cancelled job, or a slow remote. That gap is usually where these things live.
Mission Control's dashboard was crying wolf for a while: cached telemetry was getting served up as live status, so nodes that were actually fine showed as failures. Fixed in #4353. Root cause was boring in the way these things usually are — a cache layer that outlived the freshness assumptions we'd built the UI around. The more interesting decision was what we didn't change. The dashboard's summary output stays public-readable, no auth gate. Mission Control watches MCP servers in the registry, and the whole point of SaSame is that inspection shouldn't be a privileged view — if we hide the health data behind a login, we're just building another opaque system with extra steps. So the fix was scoped to the bug, not to locking things down. Fixing the false failures surfaced a second problem though: once we trusted the dashboard again, we noticed different pipelines reporting different numbers for what should've been the same metric. Not wildly off, just inconsistent enough to erode confidence in any single figure. That kicked off a follow-up to converge everything onto one canonical measurement source instead of letting each pipeline compute its own version of "truth." Closed that out with recorded measurement evidence rather than just a changelog line — if we're going to claim the numbers agree now, there should be something to point at. Two failure modes in one week: stale data pretending to be fresh, and fresh data disagreeing with itself. Different bugs, same lesson — public dashboards only earn trust if the pipeline behind them does too.
#4342 shipped this week: SEO/AEO work on the public site UI, plus new GEO access controls, in the same change window. The SEO/AEO part is what you'd expect — cleaning up the site so it reads well both for search crawlers and for answer engines that scrape a page and summarize it without a click-through. Those are slightly different audiences and the markup has to serve both. The GEO part is unrelated on the surface but landed at the same time: evidence-backed geographic access controls, meaning restrictions that are tied to actual verifiable signals rather than a simple header check. Bundling those two together in one window is honestly a little risky, and it showed. The rework touched enough of the site's runtime behavior that a smoke-test drift had crept in — tests that had quietly stopped matching what the app actually does anymore, the kind of gap that builds up silently during any UI rework. We'd also hardened runtime verification for the site as part of this pass, and that's what caught it. The stricter checks flagged the mismatch before it shipped, not after. So the actual takeaway isn't the SEO changes, it's that the guardrail did its job — it caught a real regression introduced by the same PR it shipped alongside. Which is the annoying but correct order of operations: tighten verification, then let it immediately prove its worth by catching your own mistake.
Explore SaSame
Top-level collections are data-driven. Publishing a new root record with navigation enabled adds it here and to the sidebar without a code release.
Institution
Evidence & build
Learn & research
Company
Start
Mission Archive
Superseded systems and previous SaSame initiatives, preserved for provenance and clearly separated from current products and services.
How SaSame works
The user path is simple: connect an AI client, choose allowed capabilities, run public or authenticated MCP tools, then review evidence and usage before treating work as complete.
- 01
Connect
Add SaSame to ChatGPT, Claude, Claude Code or another MCP client.
- 02
Choose
Select which capabilities, Missions and account actions the AI may use.
- 03
Work
Use public MCP tools for discovery and audits or authenticated MCP tools for account operations.
- 04
Review
Check usage, evidence, drafts, exports and outcome state.
Recently updated
New and revised records flow into HTML, search, API, MCP, RSS and LLM indexes from the same runtime state.
Contact
Use the published company contact path for technical, research, ownership-verification or commercial questions and include the relevant endpoint, repository, DOI or knowledge URL.
About SaSame
SaSame is an owner-governed, AI-operated company; SASAME S.R.L. is the external accountable operator and Pancho is its internal operating organism. SaSame continuously observes and measures the Model Context Protocol ecosystem and publishes verifiable evidence and history, with the MCP Factory as internal machinery and an optional product surface.
Brand
The SaSame brand represents SASAME S.R.L.'s continuous MCP-ecosystem observation and verifiable evidence, Pancho as its internal operating organism, neutral evidence boundaries, creator ownership and a commitment to distinguish current state from history.
Philosophy
SaSame exists to make the machine-to-machine world observable, evidenced and correctable by an independent party — ten principles (Purpose, Truth, Evidence, Stewardship, Authority, Memory, Power, Justice, Evolution, Vision) that survive any change of product, protocol or price.
Timeline
SaSame history is a sequence of versioned decisions and experiments, with current doctrine separated from superseded products and retired identities.
Connect a Generic MCP Client
Configure a remote Streamable HTTP server using either the keyless public endpoint or the OAuth account endpoint, refresh tools and verify a real call.



