cont3xt

cont3xt

Virtual Infinite Context for Agents and LLMs - maintains a continuous rolling context window, surfacing relevant memories while respecting token budgets.

Category
Visit Server

README

cont3xt

Virtual Infinite Context for Agents and LLMs
An MCP server that maintains a continuous rolling context window, always surfacing the most relevant memories for the task at hand — while respecting your token budget.


Current Status

This repository includes an MVP MCP stdio server suitable for integration with the Cline extension for VS Code. It exposes a minimal, SQLite-only toolset over stdio with zero external services required by default.

  • Version: 0.1.1
  • Transport: MCP stdio
  • Default storage: SQLite at ./data/memory.db (configurable; example config uses ./data/novel_memory.db)
  • Optional backends: Qdrant / Neo4j (disabled by default in this MVP)
  • Tools implemented:
    • memory_upsert
    • search_memory
    • context_pack
    • health_ping

Notes:

  • Tool names use underscores for compatibility with the Python server decorator. Dotted aliases (e.g., context.pack) can be added later.
  • All tools return a standard JSON envelope as text content: { "ok": boolean, "data": {...}, "meta": { "duration_ms": number, "backend": "sqlite", "version": "0.1.1" } }

Quickstart

1) Install

Requires Python 3.11+

git clone https://github.com/elevend0g/cont3xt.git
cd cont3xt
pip install -r requirements.txt
pip install -e .

2) Initialize local storage (SQLite)

virtual-context-mcp --init-db

This creates ./data/memory.db if it doesn’t exist (or the path specified by config/env).

3) Run (stdio transport)

virtual-context-mcp

This starts the MCP server over stdio.


Using with MCP Clients

Cline (VS Code)

Add an MCP server named cont3xt that launches the stdio server:

Example configuration shape (adapt for your Cline settings UI/JSON):

{
  "mcpServers": {
    "cont3xt": {
      "command": "virtual-context-mcp",
      "args": ["--config", "configs/novel_writing.yaml"],
      "env": {
        "CONTEXT_MAX_TOKENS": "12000",
        "PYTHONUNBUFFERED": "1"
      }
    }
  }
}

Notes:

  • Ensure virtual-context-mcp is in PATH (pip install -e . creates the console script).
  • The --config argument is optional; environment variables can override values (see Configuration).

Claude Desktop

{
  "mcpServers": {
    "cont3xt": {
      "command": "virtual-context-mcp",
      "args": ["--config", "configs/novel_writing.yaml"],
      "env": {
        "CONTEXT_MAX_TOKENS": "12000",
        "PYTHONUNBUFFERED": "1"
      }
    }
  }
}

Tools (MVP)

All tools return a JSON envelope as text content.

Envelope:

{
  "ok": true,
  "data": { /* tool-specific payload */ },
  "meta": {
    "duration_ms": 5.23,
    "backend": "sqlite",
    "version": "0.1.1"
  }
}

1) memory_upsert

Upsert memory for a session from either combined content or a user/assistant pair.

Arguments:

  • session_id: string (required)
  • content: string (optional; direct content)
  • user_input: string (optional; used if content not provided)
  • assistant_response: string (optional; used if content not provided)

Response (example):

{
  "ok": true,
  "data": {
    "session_id": "sess-1",
    "ids": ["b1c...f"],
    "count": 1
  },
  "meta": {
    "duration_ms": 1.23,
    "backend": "sqlite",
    "version": "0.1.1"
  }
}

2) search_memory

Simple substring search with a recency-biased score over recent SQLite chunks.

Arguments:

  • session_id: string (required)
  • query: string (required)
  • max_results: number (optional, default 10)

Response (example):

{
  "ok": true,
  "data": {
    "query": "emerald eyes",
    "results_count": 2,
    "results": [
      {
        "chunk_id": "b1c...f",
        "score": 1.7,
        "timestamp": "2025-08-09T17:30:00.000000",
        "token_count": 142,
        "preview": "User: ... Assistant: ..."
      }
    ]
  },
  "meta": {
    "duration_ms": 2.45,
    "backend": "sqlite",
    "version": "0.1.1"
  }
}

3) context_pack

Packs a token-budgeted context using recent conversation chunks. Reserves a small buffer and includes the current input if provided.

Arguments:

  • session_id: string (required)
  • current_input: string (optional, default "")
  • budget_tokens: number (optional, defaults to CONTEXT_MAX_TOKENS)

Response (example):

{
  "ok": true,
  "data": {
    "pack": {
      "schema_version": "ctx.v1",
      "budget_tokens": 12000,
      "used_tokens": 2834,
      "sections": [
        {"role": "user", "title": "Current Input", "content": "..."},
        {
          "role": "context",
          "title": "Conversation (2025-08-09T17:30:00.000000)",
          "content": "...",
          "chunk_id": "b1c...f",
          "token_count": 142
        }
      ],
      "provenance": {
        "retriever": "recent-only",
        "stores": {"sqlite": "./data/memory.db"}
      },
      "pack_stats": {
        "num_candidates": 12,
        "kept": 4,
        "dropped": 8,
        "buffer_tokens": 500
      }
    },
    "meta": {
      "input_tokens": 120,
      "output_tokens": 2834,
      "budget": 12000,
      "sources": ["b1c...f", "a9d...1"]
    }
  },
  "meta": {
    "duration_ms": 7.89,
    "backend": "sqlite",
    "version": "0.1.1"
  }
}

Notes:

  • If nothing fits within the budget (after a fixed buffer of 500 tokens), the pack includes: "reason": "BUDGET_TOO_SMALL".
  • Truncation policy: respect budget strictly; sections are assembled most-recent-first, then presented chronologically for readability.

4) health_ping

Returns basic status and configuration fingerprint.

Arguments: none

Response (example):

{
  "ok": true,
  "data": {
    "server": "cont3xt",
    "version": "0.1.1",
    "datetime": "2025-08-09T17:32:00.000000",
    "config": {
      "sqlite_path": "./data/memory.db",
      "max_tokens": 12000,
      "token_model": "cl100k_base",
      "optional_backends": {
        "qdrant": false,
        "neo4j": false
      }
    }
  },
  "meta": {
    "duration_ms": 0.41,
    "backend": "sqlite",
    "version": "0.1.1"
  }
}

Cline Demo Task (Code Gen Flow)

  1. In Cline, run a task like “Improve function X in file Y; add a unit test and make tests pass.”
  2. Cline should:
    • Call search_memory(session_id, query="project goals")
    • Call context_pack(session_id, current_input="<file diff request>", budget_tokens=12000)
    • Generate plan → apply small diff → run tests
    • Call memory_upsert with (user_input, assistant_response) to persist the session outcome
  3. Acceptance:
    • From a clean clone, pip install -e ., launch Cline, and complete a guided code edit PR in one go using the above flow.

Configuration

Defaults are provided in code, optionally loaded from a YAML file (e.g., configs/novel_writing.yaml) and overridden by environment variables.

Environment variable overrides (examples):

  • CONTEXT_MAX_TOKENS (default 12000)

  • CONTEXT_PRESSURE_THRESHOLD (default 0.8)

  • CONTEXT_RELIEF_PERCENTAGE (default 0.4)

  • CONTEXT_CHUNK_SIZE (default 3200)

  • CONTEXT_TOKEN_MODEL (default cl100k_base)

  • DATABASE_SQLITE_PATH (default ./data/memory.db)

  • DATABASE_QDRANT_URL

  • DATABASE_QDRANT_COLLECTION

  • DATABASE_NEO4J_URL

  • DATABASE_NEO4J_USER

  • DATABASE_NEO4J_PASSWORD

For the MVP, only SQLite is used. Qdrant / Neo4j are intentionally not required; future versions can enable them via env/config flags.

Truncation policy:

  • A fixed buffer of 500 tokens is reserved.
  • Packing order: include current_input (if provided) and then pack recent conversation chunks until the budget is met.
  • If no sections can be included, the pack includes "reason": "BUDGET_TOO_SMALL".

Development

Entry points:

  • Console script: virtual-context-mcp → virtual_context_mcp.main:main
  • MCP server class: virtual_context_mcp.server:VirtualContextMCPServer

Local logs: standard output (set PYTHONUNBUFFERED=1 for real-time logs). SQLite file: ./data/memory.db by default.

Run unit/integration tests as needed (note that legacy story-focused modules may not reflect the MVP surface area).


Security

  • MVP runs in a safe default mode: only persists to local SQLite.
  • No filesystem ingestion or external network writes by default.

Roadmap

  • Optional Qdrant/Neo4j integration behind env flags with graceful fallback.
  • Aliased/dotted tool names for compatibility (e.g., context.pack).
  • Richer retrieval (hybrid, deduplication), entity/graph memory, and pressure relief policies.
  • DevContainer / Docker image for reproducible environments.

License

MIT © elevend0g

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured