Velixar MCP Server
The first cognitive memory server for AI assistants. Not a vector database wrapper — a full reasoning layer that gives your AI persistent memory, a knowledge graph, identity awareness, contradiction detection, and belief tracking across every session.
Works with any Model Context Protocol client: Claude Desktop, Kiro, Cursor, Windsurf, Continue.dev, or custom hosts.
Why This Exists
Every AI assistant starts from zero every conversation. Velixar fixes that — but not by just storing and retrieving text. The MCP server gives your assistant the ability to:
- Orient itself in a workspace with a single call — no manual context assembly
- Track how beliefs evolve over time and surface when they contradict
- Build and traverse a knowledge graph of entities and relationships it discovers
- Maintain a persistent identity model of who you are, what you prefer, and how you work
- Distill sessions into durable memories automatically, with deduplication
- Import and export your entire memory corpus for backup or migration
40 tools. 5 live resources. 19 workflow prompts. One npm install.
Quick Start
npm install -g velixar-mcp-server
Get an API key at velixarai.com/settings/api-keys, then add to your MCP client:
{
"mcpServers": {
"velixar": {
"command": "velixar-mcp-server",
"env": {
"VELIXAR_API_KEY": "vlx_your_key_here"
}
}
}
}
Restart your assistant. Done.
Memory
| Tool | What it does |
|---|
velixar_store | Store a memory with tags, tier, and type |
velixar_search | Semantic search across all memories |
velixar_list | Browse with pagination and filtering |
velixar_update | Edit content or tags on an existing memory |
velixar_delete | Remove a memory |
Cognitive
| Tool | What it does |
|---|
velixar_context | Synthesized workspace briefing — orientation in one call |
velixar_identity | Get, store, or update the user's profile, preferences, and expertise |
velixar_contradictions | Surface conflicting facts or beliefs with resolution guidance |
velixar_timeline | How a topic or belief evolved over time |
velixar_patterns | Recurring problem/solution motifs across your history |
velixar_inspect | Deep inspection of a specific memory with full provenance chain |
velixar_graph_traverse | Walk entity relationships — "what connects to X?" |
velixar_distill | Extract durable memories from session content with deduplication |
Lifecycle
| Tool | What it does |
|---|
velixar_session_save | Save a session summary for later recall |
velixar_session_recall | Restore context from a previous session |
velixar_batch_store | Store up to 20 memories in one call |
velixar_batch_search | Run up to 10 search queries simultaneously |
velixar_consolidate | Merge related memories into a single durable memory |
velixar_retag | Bulk update tags across memories |
velixar_export | Export memories as JSON or Markdown, optionally with graph data |
velixar_import | Bulk import from JSON, Markdown, Notion, or Obsidian exports |
System
| Tool | What it does |
|---|
velixar_health | Backend connectivity, latency, workspace status |
velixar_debug | Cache state, circuit breaker, API timings |
velixar_capabilities | Feature list, tool inventory, resource URIs |
velixar_security | Get or set content scanning mode |
Live Resources
Resources are injected into your assistant's context automatically — no tool call needed.
| Resource | What it provides |
|---|
velixar://system/constitution | Behavioral rules and cognitive modes for the assistant |
velixar://identity/current | Your persistent user profile |
velixar://memories/recent | Most recent memories (compact) |
velixar://memories/relevant | Contextually relevant memories based on current activity |
velixar://domains/{domain}/shadow_graph | Knowledge graph view for a specific domain |
Workflow Prompts
16 built-in prompts that guide multi-step reasoning workflows:
- Orientation — recall prior reasoning, build project context, profile an entity, orient-then-narrow
- Conflict — resolve contradictions, identify knowledge gaps
- Continuity — trace belief evolution, resume sessions, reconstruct decision paths
- Lifecycle — distill sessions, consolidate topic memory, retag recent memories
- Identity — summarize user identity, detect preference shifts, align response style
- Enterprise — evaluate enterprise fit for a domain
Workspace Isolation
Memories are scoped to workspaces. Your personal project never bleeds into work.
| Priority | Source | How |
|---|
| 1 | VELIXAR_WORKSPACE_ID env var | Explicit |
| 2 | .velixar.json in project root | { "workspace_id": "my-project" } |
| 3 | Git root directory name | Automatic |
Host Compatibility
| Host | Tools | Resources | Prompts |
|---|
| Kiro CLI | ✅ | ✅ | ✅ |
| Claude Desktop | ✅ | ✅ | ✅ |
| Cursor | ✅ | ⚠️ | — |
| Windsurf | ✅ | ⚠️ | — |
| Continue.dev | ✅ | ✅ | ✅ |
When a host doesn't support resources or prompts, the server degrades gracefully — all tools still work independently.
Environment Variables
| Variable | Required | Description |
|---|
VELIXAR_API_KEY | Yes | Your API key (starts with vlx_) |
VELIXAR_WORKSPACE_ID | No | Explicit workspace scope |
VELIXAR_API_URL | No | Custom API endpoint |
VELIXAR_USER_ID | No | Explicit end-user identity. Leave unset (recommended): the API derives scope from your key — you see your own memories, same as the dashboard. Set it only when one key serves multiple named end users |
VELIXAR_DEBUG | No | true for verbose logging |
VELIXAR_LOG_FORMAT | No | json for structured Datadog/CloudWatch logging |
VELIXAR_HEALTH_PORT | No | Port for HTTP health check endpoint |
Reliability
- Automatic retry with exponential backoff (3 attempts)
- Circuit breaker — opens after sustained failures, auto-recovers
- Cache fallback — serves stale data during outages rather than failing
- Structured logging compatible with Datadog and CloudWatch
SDKs
Use Velixar directly from code:
- JavaScript/TypeScript:
npm install velixar — docs
- Python:
pip install velixar — docs
CI/CD Integration
License
MIT