The MCP server for AI agents

Bring your own agent.
We make it sharper and safer.

An MCP server that holds your keys, so your agent never has to. Connect any agent — we guard the keys, focus every request, and keep work on track, so every token does more, and work lands accurately.

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Secrets it can’t read.

Your agent works through wikiTaTa and never touches the key itself. What it can’t see, it can’t leak.
Your data. In your database.

Baseline data as a reference point — not dug out of chat history — and your source of truth going forward.
Token efficiency & monitoring.

Tokens = real money. Tracking brings visibility. Monitoring shows red flags.
Always in scope.

wikiTaTa reads the whole project, so your agent starts in the right place — every time.

Experiment in progress — chat with Alex, our AI agent, for an intelligent conversation about wikiTaTa.

Blog new white paper! the language of wikiTaTa

gives your AI

memory.

secrets it can't read.

architecture.

teams.

context.

state of affairs.

tasks.

system checks.

operations.

Project Memory

wikiTaTa gives your project a persistent memory system. Instead of important details disappearing into old chats, every decision, bug, specification, deployment note, task, and conversation becomes part of a structured knowledge base that AI and humans can continuously reference. The result is far less repeated prompting, better continuity, and a project that becomes smarter over time instead of more fragmented.

Secrets & Vault

Most AI tools ask you to paste your keys into the chat and trust the model with them. wikiTaTa doesn't: credentials live in an encrypted vault, and the same agent that does your work orchestrates them end-to-end — requesting them, walking you to where each one is issued, format- and live-testing them, and injecting them where they're needed, without ever reading the full value. It even scrubs the secrets out of the old chat transcripts you import. Encrypted at rest; every read scoped and audited; one-step rotate or revoke.

Architecture

wikiTaTa tracks how your system is actually built. APIs, services, environments, dependencies, workflows, infrastructure decisions, deployment patterns, and operational rules can all be documented and connected to the project itself. This gives AI assistants a much more accurate understanding of your stack so they can make changes with better awareness and fewer incorrect assumptions.

Teams

wikiTaTa is built for the way AI-assisted work actually happens: across multiple people, multiple sessions, and multiple agents running simultaneously. Shared memory, a unified task ledger, live presence, agent-to-agent directives, and session handoffs — multi-user is the default, not an add-on.

Context Layer

AI tools are powerful, but they usually only see the current conversation. wikiTaTa acts as the context layer between the AI and your project, allowing the system to retrieve the exact information needed at the right time. Instead of overloading the AI with massive prompts, wikiTaTa supplies focused context — helping reduce hallucinations, improve consistency, and keep work aligned with the real project state.

State Awareness

wikiTaTa keeps track of what is happening right now. Active work, pending issues, deployments, alerts, in-progress tasks, recent changes, and project health are continuously tracked so both humans and AI agents can understand the current state of the system. This allows sessions to resume cleanly and prevents important operational details from being lost between conversations.

Task Pipeline

wikiTaTa turns AI-assisted work into structured, trackable execution. Tasks can be assigned, organized, resumed, audited, and connected directly to project knowledge and operational workflows. Instead of vague chat requests scattered across sessions, work becomes persistent and coordinated — making it easier for teams and AI agents to collaborate without losing progress or duplicating effort.

System Checks

wikiTaTa continuously verifies that systems are behaving as expected. Health checks, deployment preflights, credential validation, environment comparisons, operational probes, and resilience tests help catch problems before they become outages. Rather than relying on assumptions or memory, the system actively validates the real state of the project and records the results over time.

Ops History

Every meaningful change in wikiTaTa leaves a trail. Deployments, incidents, fixes, alerts, task completions, configuration changes, security actions, and operational events are all recorded in a searchable history. This creates accountability, simplifies troubleshooting, and makes it much easier to understand how a system evolved — especially when working with multiple people or AI agents over long periods of time.

inquire

early access · by invitation

Building with AI? Let's talk.

wikiTaTa is in private early access for developers and founders building with AI. If this sounds like your project, request an invitation — every inquiry gets a personal response.

Bring your own agent.We make it sharper and safer.

Secrets it can’t read.

Your data. In your database.

Token efficiency & monitoring.

Always in scope.