Skip to main content

Pythonic ArchiveBox API Wrapper and Fast MCP Server for Agentic AI use!

Project description

Archivebox Api

CLI or API | MCP | Agent

PyPI - Version MCP Server PyPI - Downloads GitHub Repo stars GitHub forks GitHub contributors PyPI - License GitHub GitHub last commit (by committer) GitHub pull requests GitHub closed pull requests GitHub issues GitHub top language GitHub language count GitHub repo size GitHub repo file count (file type) PyPI - Wheel PyPI - Implementation

Version: 0.19.0


Table of Contents


Overview

Archivebox Api is a production-grade Agent and Model Context Protocol (MCP) server designed to interface directly with the Pythonic ArchiveBox API Wrapper and Fast MCP Server for Agentic AI use!


Key Features

  • Consolidated Action-Routed MCP Tools: Minimizes token overhead and eliminates tool bloat in LLM contexts by grouping methods into optimized, togglable tool modules.
  • Enterprise-Grade Security: Comprehensive support for Eunomia policies, OIDC token delegation, and granular execution context tracking.
  • Integrated Graph Agent: Built-in Pydantic AI agent supporting the Agent Control Protocol (ACP) and standard Web interfaces (AG-UI).
  • Native Telemetry & Tracing: Out-of-the-box OpenTelemetry exports and native Langfuse tracing.

Concept Registry

This codebase is aligned with the 5 Core Pillars Architecture of the agent-utilities ecosystem:

Concept ID Pillar Name Domain Implementation Details in archivebox-api
ECO-4.0 Ecosystem & Peripherals Tool Interface & MCP Factory Provides FastMCP server wrapper, action routing tools, and dynamic schema exposures.
ECO-4.1 Ecosystem & Peripherals A2A Network & Consensus Manages agent peer discovery, routing tables, and consensus.
OS-5.1 Agent OS Infrastructure Security & Auth Implements token-based OIDC access control, JWT filters, and Eunomia validation.
OS-5.4 Agent OS Infrastructure Telemetry & Observability Delivers warning suppressions, JSON progress logging, and error tracing.

Environment Variables

Configure the runtime environment by creating a .env file based on .env.example:

Env Variable Type Default Description
ARCHIVEBOX_BASE_URL String http://localhost:8000 Canonical endpoint URL for the backend ArchiveBox API.
ARCHIVEBOX_URL String http://localhost:8000 Fallback alias/alternative for ARCHIVEBOX_BASE_URL.
ARCHIVEBOX_USERNAME String None Username for authentication.
ARCHIVEBOX_PASSWORD String None Password for authentication.
ARCHIVEBOX_API_KEY String None API Key for token-less header authentication.
ARCHIVEBOX_TOKEN String None Pre-configured authentication token.
ARCHIVEBOX_SSL_VERIFY Boolean False Enable/disable SSL certificate validation.
AUTHENTICATIONTOOL Boolean True Toggle to enable/disable the Authentication MCP toolset.
CORETOOL Boolean True Toggle to enable/disable the Core ArchiveBox MCP toolset.
CLITOOL Boolean True Toggle to enable/disable the CLI command MCP toolset.
EUNOMIA_TYPE String none Policy mode: none, embedded, or remote.
EUNOMIA_POLICY_FILE String mcp_policies.json Path to the local policy file when using embedded mode.
ENABLE_OTEL Boolean True Enable/disable OpenTelemetry metrics/traces exporter.
OTEL_EXPORTER_OTLP_ENDPOINT String None Endpoint for the OpenTelemetry collector.

CLI or API Usage

You can use the API client programmatically in Python to manage ArchiveBox snapshots:

from archivebox_api import Api

# Initialize client
client = Api(
    url="http://localhost:8000",
    token="your-auth-token",
    verify=True
)

# Fetch snapshots
snapshots = client.get_snapshots()
for snapshot in snapshots.get("results", []):
    print(f"[{snapshot['timestamp']}] {snapshot['url']}")

Refer to docs/index.md for full developer SDK and class references.


MCP Server Setup

This server utilizes dynamic Action-Routed tools to optimize token overhead and maximize IDE compatibility.

Available MCP Tools

  • archivebox_authentication (AUTHENTICATIONTOOL=True): Manage token exchanges and validation (get_api_token, check_api_token).
  • archivebox_core (CORETOOL=True): Manage core collections (get_snapshots, get_snapshot, get_archiveresults, get_tag).
  • archivebox_cli (CLITOOL=True): Directly execute ArchiveBox command line functions (cli_add, cli_list, cli_update).

Dynamic Tool Selection & Visibility

This MCP server supports dynamic toolset selection and visibility filtering at runtime. This allows you to restrict the set of exposed tools in order to prevent blowing up the LLM's context window.

You can configure tool filtering via multiple input channels:

  • CLI Arguments: Pass --tools or --toolsets (or their disabled counterparts --disabled-tools and --disabled-toolsets) during startup.
  • Environment Variables: Define standard environment variables:
    • MCP_ENABLED_TOOLS / MCP_DISABLED_TOOLS
    • MCP_ENABLED_TAGS / MCP_DISABLED_TAGS
  • HTTP SSE Request Headers: Pass custom headers during transport initialization:
    • x-mcp-enabled-tools / x-mcp-disabled-tools
    • x-mcp-enabled-tags / x-mcp-disabled-tags
  • HTTP SSE Request Query Parameters: Append query parameters directly to your transport connection URL:
    • ?tools=tool1,tool2
    • ?tags=tag1

When query strings or parameters are supplied, an LLM-free Knowledge Graph resolution layer (using DynamicToolOrchestrator) matches query intents against known tool tags, names, or descriptions, with safe fallback and automated 24-hour background cache refreshing.


Local IDE Configuration (Cursor / Claude Desktop)

Add the following block to your mcp.json to configure stdio transport via uvx:

{
  "mcpServers": {
    "archivebox-api": {
      "command": "uv",
      "args": [
        "run",
        "--package",
        "archivebox-api",
        "archivebox-mcp"
      ],
      "env": {
        "ARCHIVEBOX_BASE_URL": "http://localhost:8000",
        "ARCHIVEBOX_USERNAME": "admin",
        "ARCHIVEBOX_PASSWORD": "your-password"
      }
    }
  }
}

Agentic AI Graph Agent

This repository features a fully integrated Pydantic AI Graph Agent. It communicates over the Agent Control Protocol (ACP) and interacts seamlessly with the Agent Web UI (AG-UI).

Running the Agent CLI

To start the interactive command-line agent:

# Export credentials
export ARCHIVEBOX_BASE_URL="http://localhost:8000"
export ARCHIVEBOX_USERNAME="admin"
export ARCHIVEBOX_PASSWORD="your-password"

# Run agent server
archivebox-agent --provider openai --model-id gpt-4o

Detailed graph node architecture explanations, custom skill configurations, and agentic trace guides are available in docs/index.md.


Security & Governance

Built directly upon the enterprise-ready agent-utilities core, standard security parameters are fully supported:

Access Control & Policy Enforcement

  • Eunomia Policies: Fine-grained, policy-driven tool authorization. Supports none, local embedded (mcp_policies.json), or centralized remote modes.
  • OIDC Token Delegation: Compliant with RFC 8693 token exchange for flowing authenticating user credentials from Web UI / ACP → Agent → MCP.
  • Scoped Credentials: Execution context runs restricted to the specific caller identity.

Runtime Security Grid

Feature Functionality Enablement
Tool Guard Sensitivity inspection with human-in-the-loop validation Enabled by default
Prompt Injection Defense Input scanning, repetition monitoring, and recursive loop blocks Enabled by default
Context Safety Guard Stuck-loop detectors and contextual overflow preemptive alerts Enabled by default

Installation

Install the Python package locally:

# Using uv (highly recommended)
uv pip install archivebox-api[all]

# Using standard pip
python -m pip install archivebox-api[all]

Contribute

Contributions are welcome! Please ensure code quality by executing local checks before submitting pull requests:

  • Format code using ruff format .
  • Lint code using ruff check .
  • Validate type-safety with mypy .
  • Execute test suites using pytest

Available MCP Tools

Tool Module Toggle Env Var Enabled by Default Description & Nested Methods
Authentication AUTHENTICATION_TOOL True Register authentication management tools.
CONCEPT:OS-5.1 — Security & Auth Action-routed methods: `check_api_token`, `get_api_token`. |

| Core | CORE_TOOL | True | Manage archivebox core operations. Action-routed methods: get_any, get_archiveresults, get_snapshot, get_snapshots, get_tag. | | Cli | CLI_TOOL | True | Manage archivebox cli operations. Action-routed methods: cli_add, cli_list, cli_remove, cli_schedule, cli_update. |

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

archivebox_api-0.19.0.tar.gz (31.4 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

archivebox_api-0.19.0-py3-none-any.whl (36.4 kB view details)

Uploaded Python 3

File details

Details for the file archivebox_api-0.19.0.tar.gz.

File metadata

  • Download URL: archivebox_api-0.19.0.tar.gz
  • Upload date:
  • Size: 31.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.14.4

File hashes

Hashes for archivebox_api-0.19.0.tar.gz
Algorithm Hash digest
SHA256 fd46880226676bba2f014a6799183e386eb47c791b001df483254bb85cccf375
MD5 221f83580c03e31730d9842b22eecd2a
BLAKE2b-256 63f6c4545fd2abcea4ca97e09e1ca0af73551b46f40bcd74b6479a21ec7f14d2

See more details on using hashes here.

File details

Details for the file archivebox_api-0.19.0-py3-none-any.whl.

File metadata

File hashes

Hashes for archivebox_api-0.19.0-py3-none-any.whl
Algorithm Hash digest
SHA256 744cd182dbeb531444c1e252f3ce4f23e4b9c0711fb18083a44d39309c24aa48
MD5 6a5c3c2059fa0dfb9573fe3ca0efa521
BLAKE2b-256 39e5e2fdce98c9b4c3cb70bad4520fdf772996593920324a0b225e5e594c8123

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page