Project Memory
Read durable project context: architecture notes, constraints, and verified setup state.
SVG and CSS mesh fallback, premium without external media.
ANANSI-MNEMO / AI Agents / MCP
Your AI now remembers your system.
Build a persistent brain for delivery teams: live context retrieval, portable skills, and auditable operations that survive every session and every assistant.
- Read-only defaults
- Scoped permissions
- No secrets in vault
- Auditable runs
Capabilities
What your AI can access
ANANSI-MNEMO keeps your execution context durable: memory, decisions, technical fixes, and operational reports in one queryable surface.
Decision History
Trace why key technical and product choices were made, with linked rationale and versions.
Resolved Fixes
Reuse known fixes for recurring bugs and reduce repeated debugging loops across sessions.
Team Conventions
Apply agreed coding rules, naming patterns, and delivery standards without prompt drift.
Operational Reports
Surface weekly health metrics, anomalies, and maintenance outputs from your brain workflows.
Knowledge Ingestion
Convert talks, calls, docs, and media into structured notes that stay queryable by agents.
Integration
Two ways to power your AI
MCP Runtime Access
Connect your AI runtime to live context so assistants can answer from real project data, not static prompts.
- Read-only by default for safe analysis workflows.
- Fine-grained permissions for tools and datasets.
- Context retrieval inside normal conversations.
Agent Skills Pack
Ship portable skill bundles and DESIGN.md contracts to keep behavior consistent across Claude, Codex, and ChatGPT.
- Reusable capabilities with clear scopes.
- Design and token alignment across agents.
- Faster onboarding for new projects and teammates.
Trust and Safety
Operational trust by design
- Read-only defaults for retrieval and reporting flows.
- Scoped permissions per tool, dataset, and runtime.
- No secrets, tokens, or credentials stored in the vault.
- Traceable logs for critical actions and updates.
Agent orchestration snapshot
A practical sequence: memory update, operational check, delivery handoff, then trust validation.
Memory Agent New implementation detected. Logging the decision, affected modules, and verification status into the project brain.
Ops Agent Daily maintenance report generated. Anomaly check passed. Follow-up automation is queued for the next cycle.
Delivery Agent Preparing implementation summary with lint, typecheck, and build evidence for release handoff.
Audit Agent Permission scopes validated. Read-only retrieval remains active for this workflow. No secrets persisted in notes.
Team Paths
How teams deploy
Founder
Decide Faster, With Proof
Move from scattered notes to an operational brain that supports product and revenue decisions.
- Single source of truth for system direction.
- Clear execution priorities across teams.
- Lower risk from context loss between sessions.
Ops Lead
Run Reliable Automation
Control recurring workflows with auditable runs, stable procedures, and explicit handoff points.
- Fewer manual follow-ups and duplicate tasks.
- Visible status for maintenance and anomalies.
- Safer operations with scoped access defaults.
Developer
Build With Persistent Context
Implement faster by querying prior decisions, fixes, and architecture notes directly in your workflow.
- Reduced rework across sessions and agents.
- Stronger consistency with project conventions.
- Higher confidence before deploy and release.
FAQ
Technical questions, clear answers
The baseline is practical: context first, strict permissions, and a deployment path that works with real teams and real systems.
Can ANANSI-MNEMO modify production systems directly?
Not by default. The baseline setup is read-only retrieval and reporting. Write actions are opt-in, scoped, and audited.
Do we need one tool for every AI assistant?
No. The model is shared: MCP for live context and Skills/DESIGN.md for portable behavior across assistants.
What happens if media assets are missing?
The page keeps a premium experience through SVG/CSS mesh fallbacks. Videos are progressive enhancements only.
How quickly can a team start?
Most teams start with project memory + one automation loop, then add skills packs and stricter governance in phases.
Final CTA
Build on durable context, not repeated prompts.
Launch ANANSI-MNEMO with MCP runtime access, skills portability, and governance defaults that keep agent execution reliable.