Best for
- Developers who value privacy and want a local-first workflow
- AI agent users who need reliable tool routing and verification
- Teams that need cross-session memory and knowledge graphs
P
60FMRS · C
Prism Coder is a feature-rich MCP server offering persistent memory, local inference, and advanced verification. Ideal for local-first workflows, but setup may require managing multiple components.
Prism Coder is an MCP server that provides long-term memory across sessions for AI tools like Claude, Cursor, Gemini CLI, and Codex. It ships with an open-weight model fleet (2B–27B) for fast, offline tool routing, no cloud required. The free local tier offers persistent session memory (knowledge graph, session ledger, time travel), cognitive routing, multi-agent hivemind, behavioral verification, and drift detection. Paid subscriptions unlock cloud sync, higher model tiers, and team features. The server also includes a CLI for connecting multiple hosts, model management, and local browser testing.
Tools
session_bootstrap
Hook-free first-turn greeting and dashboard-configured context.
session_load_context
Explicit project reload or older-server startup fallback.
session_save_ledger
Append an immutable session log entry.
session_save_handoff
Save live state for the next session.
knowledge_search
Semantic + keyword search over all memories.
query_memory_natural
Memory-first Q&A with a grounded live-source fallback on paid tiers.
session_detect_drift
Detect when a session has drifted from its goal.
verify_behavior
Pre-edit scenario challenge — catch bad changes before they happen.
knowledge_ingest
Teach Prism a codebase or document.
prism_infer
Local-first inference (route/chat/code modes, thinking, cloud escalation).
inference_metrics
Session delegation or persisted MCP + VS Code panel local/cloud stats.
Setup
- Install the npm package globally:
npm install -g prism-mcp-server. - Run
prism connectto auto-detect and register Claude Code, Claude Desktop, Cursor, Gemini CLI, and Codex. Use--host <name>to target a specific host,--dry-runto preview changes. - Restart your MCP hosts.
- (Optional) Pull local models:
ollama pull dcostenco/prism-coder:2b,:4b,:9b, or:27b. - (Optional) Set environment variables like
BRAVE_API_KEY,GEMINI_API_KEY,SUPABASE_URL, etc.
Fit and risk
Not for
- Users who need full cloud features without a Synalux subscription
- Those who need to run large models on modest hardware (27B requires ~16GB)
- Scenarios requiring official vendor support
Required permissions
- Filesystem access to read/write local SQLite database and config files
- Network access for Brave Search, Gemini AI, Supabase cloud sync, and Synalux portal
- Execution of local Ollama models for inference
Risks and side effects
- Local storage may contain sensitive data; encryption recommended
- Cloud features require API keys which could leak if mishandled
- Model outputs may hallucinate; verification is essential
- Local model routing may lead to stale information if context not managed properly
Troubleshooting
- Ensure all required environment variables are set (e.g., `BRAVE_API_KEY`, `GEMINI_API_KEY`)
- Run `prism connect --dry-run` to check changes
- Restart MCP hosts to apply config
- Check that local Ollama service is running and accessible
- Consult docs and issue tracker for known issues
Use cases
Coding assistants that retain project context and decisions across sessions
Offline-first AI tool routing with local models
Multi-agent coordination with shared project memory
Reliable AI edits with verification and drift detection
Supported clients
Claude DesktopFull support
Claude CodeFull support
CursorFull support
Gemini CLIFull support
CodexFull support