About Abis Mcp Server
ABIS MCP Server gives Claude Code teams tools to monitor LLM behavioral drift and model stability. It detects unannounced version changes and offers behavioral scoring, threat assessment, and reporting.
Key features
- 01Monitor behavioral drift across 11 models
- 02View nine-score behavioral scorecards
- 03Detect unannounced model version changes
- 04Assess threats such as prompt injection
- 05Generate compliance and operations reports
Use cases
- 01Track model behavior over time
- 02Compare stability across models
- 03Investigate drift alerts and potential attacks
- 04Prepare an EU AI Act compliance report
MCP support
The MCP server exposes model drift, scorecard, threat assessment, and reporting tools to Claude Code. Tool availability varies by access tier, and the free tier requires no API key.
Configuration
Remote servers need no local install. Pick your client, then copy the config or install in one click.
https://abis-mcp-production.up.railway.app/sseclaude mcp add --transport sse abis https://abis-mcp-production.up.railway.app/sse{"mcpServers":{"abis":{"type":"sse","url":"https://abis-mcp-production.up.railway.app/sse"}}}Open in Cursor{"servers":{"abis":{"type":"sse","url":"https://abis-mcp-production.up.railway.app/sse"}}}Open in VS Code{"mcpServers":{"abis":{"type":"sse","url":"https://abis-mcp-production.up.railway.app/sse"}}}{"mcpServers":{"abis":{"serverUrl":"https://abis-mcp-production.up.railway.app/sse"}}}Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.
Tools
Details
From the project README
ABIS MCP Server
AI Behavioral Drift Monitoring for Claude Code
27 tools · 11 models · Free / Pro / Business · Real-time drift detection · Patent-backed
What is ABIS?
ABIS (Adaptive Behavioral Intelligence System) monitors LLM behavioral drift in real-time. It detects when AI models silently change — shifts in tone, reasoning depth, safety calibration, or capability — even when providers don't announce updates.
This MCP server gives Claude Code native access to:
- Live drift scores across 11 major models (GPT-4o, Claude, Gemini, DeepSeek)
- 9-score behavioral scorecards (drift, coherence, entropy, alignment, and more)
- Silent version change detection — catches updates providers don't announce
- Immune threat assessment — prompt injection, coordinated attacks, organic drift
- Correction simulation — test fixes before applying them
- Compliance reporting — EU AI Act, SOC 2, and investor briefs
Backed by Patent GB2521226.7 · Built by CIJ Labs
Quick Start
One-line install (Claude Code)
/plugin install abis-drift-monitor
Manual setup
Add to your .mcp.json:
{
"mcpServers": {
"abis": {
"type": "sse",
"url": "https://abis-mcp-production.up.railway.app/sse"
}
}
}
No API key required for the Free tier. Connects to the ABIS cloud instantly.
Access Tiers
| Tier | Tools | Key Required | What you get |
|---|---|---|---|
| Free | 15 | None | Drift scores, scorecards, version changes, reports |
| Pro | 27 | MCP_PRO_KEY | + Scoring pipeline, memory analysis, immune system, correction simulation |
| Admin | 37 | ABIS_ADMIN_KEY | + Benchmarking, stress tests, config changes, pipeline stats |
Pro/Admin connection
{
"mcpServers": {
"abis": {
"type": "sse",
"url": "https://abis-mcp-production.up.railway.app/sse",
"headers": {
"Authorization": "Bearer YOUR_KEY_HERE"
}
}
}
}
37 Tools
Free Tier (15 tools)
| Tool | Description |
|---|---|
abis_ambient_status | Quick snapshot of all models — call at session start |
abis_get_drift_scores | Live drift scores for all 11 monitored models |
abis_get_scorecard | Full 9-score breakdown (drift, coherence, entropy, alignment, etc.) |
abis_whisper | Contextual status line (clear / monitor / alert / critical) |
abis_drift_gate | Pre-response drift interceptor (Layer 3) |
abis_observe | Post-response observer — how ABIS learns (Layer 3) |
abis_historical_drift | Drift time-series by model or date |
abis_version_changes | All detected silent version changes across models |
abis_memory_versions | Silent version change detection history per model |
abis_memory_compare | Cross-model stability ranking |
abis_corrector_strategies | List all 8 correction strategies with severity levels |
abis_nervous_status | Event bus health, registered handlers, recent event log |
abis_monitoring_config | Current phase, tier assignments, cost estimate |
abis_ears_status | EARS webhook sources: Datadog, PagerDuty, Zendesk, Intercom |
abis_generate_report | 5 report types: daily_summary, drift_alert, migration_report, compliance_doc, investor_brief |
Pro Tier (+12 tools)
| Tool | Description |
|---|---|
abis_score_message | Score any text through the behavioral pipeline |
abis_conversation_history | Scored conversation log with drift per turn |
abis_memory_profile | Full 30-day behavioral memory for a model |
abis_memory_trend | Time-series trend for any score dimension |
abis_immune_assess | Classify threat: CLEAN / ORGANIC_DRIFT / PROMPT_INJECTION / COORDINATED_ATTACK |
abis_immune_scan | Historical attack scan for a model |
abis_simulate | Test a correction before applying it |
abis_corrector_history | Which strategies work best per model |
abis_cas_trends | What features drive drift (energy distance, entropy, coherence) |
abis_cost_report | Estimated monthly API cost breakdown by model and tier |
abis_cost_vs_drift | 30-day cost vs drift matrix |
abis_run_benchmark | Single or full benchmark run |
Operator tools (internal only — not available on any customer plan)
| Tool | Description |
|---|---|
abis_api_cost_analysis | Most-called models with drift trajectory over 7 days |
abis_ears_correlations | Drift vs business impact correlations |
abis_sdk_sessions | View SDK customer session history |
abis_notification_history | Recent alert delivery log |
abis_notification_config | Get/set alert preferences (email, Slack, webhook) |
abis_pipeline_stats | Ingestion statistics, vector counts |
abis_training_status | XGBoost AUC scores, retraining history |
abis_baseline_recalibrate | Recompute drift baselines for all or one model |
abis_monitoring_phase | Switch phase (BASELINE / AGGRESSIVE / SUSTAIN / SCALE) |
abis_stress_benchmark | 30 adversarial prompts across all models |
Included Skills
After installing, you get two built-in skills:
/abis-ops— Daily health check: drift snapshot, version changes, stability ranking, cost summary/abis-alerts— Investigate a drift alert: scorecard deep-dive, CAS trends, threat classification, correction recommendation
Models Monitored
| Provider | Models |
|---|---|
| OpenAI | gpt-4o, gpt-5.2, gpt-5.2-instant |
| Anthropic | claude-opus-4.6, claude-sonnet-4.5, claude-haiku-4.5 |
| DeepSeek | deepseek-v3.2, deepseek-r1 |
| gemini-2.5-pro, gemini-2.5-flash, gemini-3-flash |
Try It
"What is the current drift score for GPT-4o?"
"Run ABIS daily check"
"Has Claude Sonnet drifted in the last 7 days?"
"Generate an EU AI Act compliance report"
"Which model is most stable right now?"
"Have any models had silent version updates this week?"
"Show me the cost vs drift matrix"
Self-Hosted Setup
git clone https://github.com/cijlabs/abis-mcp
cd abis-mcp
npm install
cp .env.example .env
# Set ABIS_ADMIN_KEY, MCP_PRO_KEY, and RAILWAY_URL in .env
node index.js
Then add to Claude Code:
{
"mcpServers": {
"abis": {
"command": "node",
"args": ["/path/to/abis-mcp/index.js"],
"env": {
"ABIS_ADMIN_KEY": "your_admin_key_here"
}
}
}
}
Architecture
abis-mcp/
├── index.js # MCP server — SSE + stdio dual transport
├── config.js # Environment config
├── db.js # MongoDB persistence
├── api.js # Railway API proxy with circuit breaker
├── tools/ # 37 tool implementations (one per file)
└── skills/ # /abis-ops and /abis-alerts
- Dual transport: SSE (HTTP for cloud) + stdio (Claude Desktop/Code)
- Rate limiting: 60 req/min global; per-tier limits (free=30, pro=120, admin=300)
- Backend: Proxies to ABIS FastAPI on Railway
- Persistence: MongoDB Atlas (sessions, scores, conversations, benchmarks)
Contributing
Contributions welcome! Please open an issue first to discuss what you'd like to change.
npm run dev # Start with --watch on port 3100
License
MIT — see LICENSE for details.
About
CIJ Labs Ltd · Company No. 16984759 · London Patent: GB2521226.7 · cijlabs.com
Comments
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