Cognipeer Console MCP server
Commit Nov 13, 2026An open-source AI gateway and control plane that provides LLM routing, RAG, MCP hub management, and agent observability for multi-tenant teams.
Also known as Cognipeer/console
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- 27
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- Downloads, 30 days
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- Latest version
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- Last commit
- Nov 13, 2026
- License
- AGPL-3.0
What is Cognipeer Console MCP?
Cognipeer Console is an open-source AI gateway and control plane that provides LLM routing, RAG, MCP hub management, and agent observability for multi-tenant teams.
Summary generated from the project's README
About Cognipeer Console MCP server
Managing multi-tenant AI infrastructure and agent workflows is what Cognipeer Console enables for engineering teams. This self-hosted, open-source gateway acts as a central control plane for routing LLM requests across providers like OpenAI, Anthropic, AWS Bedrock, and Google Vertex AI. It provides an OpenAI-compatible interface for chat completions, embeddings, and batch operations, allowing developers to implement fallback chains and per-model rate limiting through a unified API.
Beyond simple routing, the platform serves as an MCP hub to host and discover Model Context Protocol servers. It includes a comprehensive RAG engine for document ingestion and vector store management using providers such as Pinecone, Chroma, or Qdrant. Users can monitor their entire ecosystem through agent tracing and inference monitoring. The system is designed for security-conscious environments, utilizing the Cedar policy engine for granular authorization and offering guardrails for PII detection and content moderation.
What you can do with it
- 1Centralize LLM provider accessRoute requests through a single OpenAI-compatible endpoint to access multiple models like Anthropic or Bedrock.
- 2Manage Model Context Protocol serversCurate and host various MCP servers to provide tools and context to your AI agents.
- 3Implement RAG pipelinesIngest documents and manage vector databases to provide retrieved context to your models.
- 4Monitor agent performanceTrack the execution steps of your agents using streaming or batch tracing.
Written from the project's README. Every use case is checked against a quote from it.
Automated checks
Ran Nov 14, 2026Full report →Not verified yet. A server needs a score of 80, no serious finding, and enough data for us to check. How checks work · What to fix for more points
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- Open source license (OSI)AGPL-3.0spdx.org/licenses/AGPL-3.0.html ↗Pass
- Commit or release in the last yearLast commit or release 2026-11-13github.com/cognipeer/console ↗Pass
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README
View on GitHubCognipeer Console
Self-hosted, open-source AI gateway and control plane: OpenAI-compatible LLM routing, RAG, an MCP hub, guardrails and agent tracing for multi-tenant teams.
Docs · Quick start · Discussions · Changelog · Contributing · Contact
Adoption: in active use at 15 companies that Cognipeer supports as enterprise customers. Open-source users are not included in this count.
Community edition is available under AGPL-3.0. Commercial licensing, hosted deployments, and support agreements are available separately through Cognipeer.
Features
Gateway
- LLM Gateway — OpenAI-compatible chat completions, embeddings, batch, and moderations across OpenAI, Anthropic, AWS Bedrock, Google Vertex AI, vLLM, Ollama, and more
- Model Hub & Dynamic Routing — Fallback chains and per-model quota/rate limiting
- Realtime (Enterprise) — WebSocket voice agents with barge-in and tool-call events
Agents & Automation
- MCP Hub — Curate, host, and discover Model Context Protocol servers (OpenAPI, remote, stdio) with per-tool controls
- Sandbox (Enterprise) — Isolated runtime environments for code, agents and previews with snapshot/fork/resume and port-forwarded previews
- Browser Automation — Managed browser profiles, live sessions, and per-browser MCP endpoints
- A2A Protocol — Publish Console-managed agents as Agent-to-Agent servers with agent cards
- Prompt Management — Versioned templates with environment-based deployment (dev/staging/prod); the Prompt Optimizer is Enterprise
Knowledge & Retrieval
- RAG / Knowledge Engine — Document ingestion, chunking, embedding, and retrieval
- Web Crawler & Web Search — Scheduled or ad-hoc crawling plus a built-in search provider
- Vector Store Management — Multi-provider vector operations (Pinecone, Chroma, Qdrant, and more) with built-in SQLite vector support
- OCR & Rerankers — Layout/table-aware document extraction and Cohere-compatible reranking
- Semantic Memory — Scoped memory stores with vector-based recall
Observability & Evaluation
- Agent Tracing — Batch and streaming ingest, OTLP/HTTP JSON, and an OpenTelemetry exporter
- Evaluations — Datasets, AI-assisted labeling, and accuracy scoring
- Inference Monitoring & Alerts — Real-time monitoring for self-hosted inference servers with rule-based alerting
Safety & Compliance
- Authorization Engine — Roles, group grants, project permissions and API token scopes are decided by one policy engine (Cedar) on every request, with custom allow/deny policies, an access check, decision ids on every refusal and an audit trail (docs)
- Guardrails — PII detection, content moderation, prompt shields, and custom LLM-based evaluators
- AI Red-Teaming — OWASP LLM Top 10 probes, campaigns, and attack runs
- Audit Logging — Tenant-scoped audit trails
Infrastructure & Cost
- GPU Fleet (Enterprise) — Pooled GPU inference with MIG slicing, Hugging Face catalog deploys, and capacity planning
- Cost & Optimization (Enterprise) — Budgets and automated optimization prescriptions on top of spend and usage tracking
- Multi-Tenant Architecture — Complete data isolation per tenant, projects and groups; SSO (OIDC) and LDAP sign-in are Enterprise
- File Management — Multi-provider file storage with automatic Markdown conversion
- Quota & Rate Limiting — Multi-dimensional quota enforcement with plan-level defaults
Editions
This repository is the Community Edition, licensed under AGPL-3.0. The commercial Enterprise Edition adds Sandbox, Realtime, GPU Fleet, Cluster (multi-node), Cost & Optimization, Prompt Optimizer, AI App Gateway, Portals, Channels, Service Reports, Entity Health, Data Retention, Single Sign-On (OIDC) and LDAP Directory. In a community build these pages show an upgrade notice. See COMMERCIAL.md for commercial terms.
Quick Start
Prerequisites
- Node.js 20+
- npm
Installation
git clone https://github.com/Cognipeer/console.git
cd console
npm install
cp .env.example .env.local
npm run dev
Set JWT_SECRET and PROVIDER_ENCRYPTION_SECRET in .env.local to two different random values of at least 32 characters (for example openssl rand -hex 32). Development starts without them and logs a warning; production refuses to start.
The gateway starts with SQLite by default — no external database required.
Visit http://localhost:3000 to access the dashboard.
Docker
Docker Compose reads its variables from .env. Create it with two independent secrets, then start:
printf 'JWT_SECRET=%s\nPROVIDER_ENCRYPTION_SECRET=%s\n' "$(openssl rand -hex 32)" "$(openssl rand -hex 32)" > .env
docker compose up -d
Or build and run manually with the same .env:
docker build -t cognipeer-console .
docker run -p 3000:3000 -v ./data:/app/data --env-file .env cognipeer-console
Keep both values: changing PROVIDER_ENCRYPTION_SECRET later makes stored provider credentials unreadable, and changing JWT_SECRET signs everyone out.
Architecture
┌────────────────────────────────────────────────────┐
│ Next.js App │
├──────────────┬──────────────┬──────────────────────┤
│ Dashboard │ Client API │ Dashboard API │
│ (UI) │ /client/v1/* │ /api/* │
├──────────────┴──────────────┴──────────────────────┤
│ Middleware │
│ (JWT Auth + Feature Gates + CORS) │
├────────────────────────────────────────────────────┤
│ Service Layer │
│ Models │ Vector │ Knowledge Engine │ Memory │ Tracing │
├────────────────────────────────────────────────────┤
│ Provider Registry │
│ Contracts → Runtimes (LLM, Vector, File) │
├────────────────────────────────────────────────────┤
│ Database Abstraction │
│ SQLite (default) │ MongoDB │
├────────────────────────────────────────────────────┤
│ Core Infrastructure │
│ Config │ Logger │ Cache │ Resilience │ Health │
└────────────────────────────────────────────────────┘
Technology Stack
- Framework: Next.js 15 (App Router) + TypeScript
- UI: Mantine v8 + Tailwind CSS
- Database: SQLite (default, zero-dependency) or MongoDB
- Auth: JWT (jose) + API tokens
- Authorization: Cedar policy engine (WebAssembly) deciding every request
- Cache: None / Memory / Redis
- Logging: Winston with structured context
Configuration
All configuration is managed through environment variables. See .env.example for the full list.
Key variables:
| Variable | Default | Description |
|---|---|---|
DB_PROVIDER |
sqlite |
Database backend (sqlite or mongodb) |
JWT_SECRET |
— | Required. Secret for JWT signing |
MAIN_DB_NAME |
cgate_main |
Main database name |
CACHE_PROVIDER |
memory |
Cache backend (none, memory, redis) |
RATE_LIMIT_PROVIDER |
mongodb |
Rate limit backend (mongodb, memory, redis) |
BROWSER_BLOCK_PRIVATE_NETWORK |
true |
Block private-network egress from managed browser sessions |
CORS_ENABLED |
false |
Enable CORS for client APIs |
TRUSTED_PROXIES |
— | Reverse proxies or load balancers whose X-Forwarded-For is trusted; token IP allowlists and IP rules in access policies depend on it |
For the full configuration reference, see the Configuration Guide.
Client API
The gateway exposes an OpenAI-compatible API at /api/client/v1/:
# Chat completion
curl -X POST http://localhost:3000/api/client/v1/chat/completions \
-H "Authorization: Bearer <API_TOKEN>" \
-H "Content-Type: application/json" \
-d '{"model": "gpt-4", "messages": [{"role": "user", "content": "Hello"}]}'
# Embeddings
curl -X POST http://localhost:3000/api/client/v1/embeddings \
-H "Authorization: Bearer <API_TOKEN>" \
-H "Content-Type: application/json" \
-d '{"model": "text-embedding-3-small", "input": "Hello world"}'
See openapi.yaml for the full API specification.
Official SDK
If you are building an application against Cognipeer Console, prefer the official TypeScript/JavaScript SDK:
- SDK repo: console-sdk
- SDK docs: docs.cognipeer.com/console-sdk
Use this repository and its docs for platform setup, deployment, providers, tenancy, auth, and raw HTTP API semantics.
Documentation
Full documentation is available in the docs/ directory:
- Getting Started
- Architecture
- Configuration
- Deployment
- Multi-Tenancy
- Authorization and Upgrading to the policy engine
- API Reference
- Licensing
- Security
Build and preview the documentation site:
npm run docs:dev
Contributing
See CONTRIBUTING.md for development guidelines, code style, and PR checklist.
Security
Security reporting guidance is in SECURITY.md. Do not disclose vulnerabilities in public issues.
Cognipeer open-source projects
| Project | What it does |
|---|---|
| console-sdk | TypeScript SDK for the Cognipeer Console API |
| agent-sdk | Lightweight, message-first agent runtime |
| agent-server | Ready-made REST API layer for AI agents |
| chat-ui | React chat UI components for AI agents |
| to-markdown | Convert PDF, Office, HTML and more to Markdown for LLM pipelines |
| graph-builder | Turn text sources into a queryable graph |
| cognipeer-observability | Drop-in agent tracing for LangChain, LangGraph, OpenAI Agents and OpenTelemetry |
If this project is useful to you, a ⭐ on GitHub helps other developers find it.
Questions or enterprise support: developer@cognipeer.com.
License
This repository is licensed under the GNU Affero General Public License v3.0. See LICENSE for the full text.
If you want to embed Cognipeer Console in a closed-source product, offer a proprietary hosted derivative without AGPL obligations, or purchase support/SLA coverage, see COMMERCIAL.md
Cognipeer Console MCP questions
What is the license for the community edition?
The community edition is available under the AGPL-3.0 license.
Does the gateway require an external database to start?
No, the gateway starts with SQLite by default, so no external database is required for initial setup.
What features are included in the Enterprise Edition?
The Enterprise Edition includes Sandbox, Realtime, GPU Fleet, Cluster, Cost & Optimization, Prompt Optimizer, and Single Sign-On (OIDC) and LDAP.
Can I use this with OpenAI-compatible tools?
Yes, the gateway provides OpenAI-compatible chat completions, embeddings, batch, and moderations.