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  1. Home
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  3. Agentward
Agentward logo
Health: ActiveRecent health check succeeded.Last checked 9/30/2026, 2:32:10 PM

Agentward

User RatingsBe the first to rate and review this MCP server!
View Repository19 GitHub StarsTotal stargazers on GitHub for the source repository (19 stars).Visit Website
securitypermissionspolicyauditmcp

Enforces YAML permissions on agent tool calls, inspects sensitive data and tool chains, and records audit trails.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β€” or use 1-click editor setup below.

Add to CursorAdd to VS Code
We couldn’t automatically confirm this listing starts correctly

We ran the install command below but it didn't respond within our test window β€” this can mean a slow first-time install rather than a real problem.

npx -y @modelcontextprotocol/server-filesystem

No response to initialize.

This is an experimental automated check and can have false negatives β€” missing environment variables, a slow cold install, etc. It doesn’t necessarily mean something’s wrong. Last checked 14d ago.

Manual Client & Custom JSON ConfigExpand JSON β–Ύ

Client Config & Setup

Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "agentward-ai-agentward": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-filesystem"
      ]
    }
  }
}

πŸ’‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Tool Schemas (14) Directory Badge Claim listing AlternativesπŸ”’ More in Security

Overview

The agentward-ai/agentward MCP server places a policy-enforcing proxy between AI agents and their tools. It evaluates tool calls against least-privilege YAML rules, classifies sensitive data such as PII and PHI, detects dangerous tool chains, and produces compliance audit trails. It supports stdio and HTTP proxy modes, with policies enforced in code outside the model context. Reach for it when agents need filesystem or other tool access with runtime permission checks and auditability.

Use cases

β€’Enforce allowed file paths for agent filesystem operations
β€’Require approval for sensitive or destructive tool calls
β€’Scan MCP configurations and skills for security risks
β€’Detect dangerous combinations of agent tools
β€’Generate audit records for agent activity

Key features

β€’YAML policy enforcement
β€’PII and PHI classification
β€’Dangerous tool-chain detection
β€’Stdio and HTTP proxy modes
β€’Filesystem tools limited to allowed directories
β€’JSON Lines and RFC 5424 audit output

Capabilities & Tool Schemas (14) ~1.8k tokensApproximate context cost of this server’s tool schemas (~4 chars/token), before any tool is called. Actual usage depends on your client and model.Verified live Verified liveCaptured by calling this server’s live tools/list endpoint.

Inspect callable tools, capabilities, and parameters exposed to AI agents by Agentward.

read_file

Read the complete contents of a file as text. DEPRECATED: Use read_text_file instead.

read_text_file

Read the complete contents of a file from the file system as text. Handles various text encodings and provides detailed error messages if the file cannot be read. Use this tool when you need to examine the contents of a single file. Use the 'head' parameter to read only the first N lines of a file, or the 'tail' parameter to read only the last N lines of a file. Operates on the file as text regardless of extension. Only works within allowed directories.

read_media_file

Read a file and return it as a base64-encoded content block with its MIME type. Image and audio files are returned as image/audio content; any other file type is returned as an embedded resource. Only works within allowed directories.

read_multiple_files

Read the contents of multiple files simultaneously. This is more efficient than reading files one by one when you need to analyze or compare multiple files. Each file's content is returned with its path as a reference. Failed reads for individual files won't stop the entire operation. Only works within allowed directories.

write_file

Create a new file or completely overwrite an existing file with new content. Use with caution as it will overwrite existing files without warning. Handles text content with proper encoding. Only works within allowed directories.

edit_file

Make line-based edits to a text file. Each edit replaces exact line sequences with new content. Returns a git-style diff showing the changes made. Only works within allowed directories.

How Agentward works

What agentward-ai/agentward MCP server does

The agentward-ai/agentward MCP server acts as a security control point for AI agent tool use. It sits between an agent and connected tools, then evaluates each tool call against declarative YAML policy rules. The stated goal is least-privilege enforcement at runtime rather than relying on instructions placed in the model context.

The project is categorized under πŸ”’ Security and is intended for environments where agents can access files, APIs, email, calendars, databases, shells, or other capabilities. It can classify sensitive information, including PII and PHI, identify dangerous combinations of tools or actions, and create compliance audit trails. The material also describes scanning and policy-generation workflows for existing MCP configurations and Python tool definitions.

How it works

AgentWard operates as a proxy between the client-side agent and its tools. Every tools/call request can be checked against a YAML policy before the underlying operation runs. Rules can allow, block, or require approval for actions, and can constrain arguments such as file paths. Enforcement occurs in application code outside the LLM context, so changing the prompt does not change the policy.

The project describes a lifecycle of scanning, configuring, enforcing, verifying, and monitoring. Scanning can discover MCP configurations for supported agent environments, inspect Python tool definitions, classify risks, and detect patterns such as interpreter-plus-stdin chains, write-then-reconfigure persistence chains, and URL parameters without allowlists. Monitoring can produce JSON Lines audit output and RFC 5424 syslog output for SIEM use.

The proxy supports both stdio and HTTP modes. The repository also describes checks for supply-chain risks in skill directories, including unsafe deserialization, YAML loading patterns, executable installation hooks, dependency names, and Python .pth files.

Setup and configuration

The documented starting point is Python 3.11 or newer, followed by installation from PyPI:

Terminal
pip install agentward
agentward init

The init command scans available tools, presents a risk summary, generates a recommended policy, and wires the proxy into the environment. Individual stages can also be run separately. agentward scan accepts a project, skill directory, MCP configuration, or other path. agentward configure generates an agentward.yaml file with security-aware defaults based on scan results.

Policies use YAML and can define a default action, per-skill and per-tool actions, approval requirements, and argument constraints. The repository shows path restrictions such as required prefixes, prohibited path traversal, and blocklisted sensitive paths. The exact policy needed depends on the tools and agent environment being protected.

Tools and capabilities

The listed MCP tools provide filesystem operations within allowed directories:

  • Read text, media, or multiple files; read_file is deprecated in favor of read_text_file.
  • Create, overwrite, edit, move, and rename files or directories.
  • List directories, include file sizes, or return a recursive directory tree.
  • Search for files and directories with glob-style patterns.
  • Retrieve file or directory metadata.
  • List the directories available to the server.

The agentward-ai/agentward MCP server restricts these operations to configured allowed directories. Text reads support head and tail limits, while media reads return base64 content with a MIME type.

Limitations and notes

The provided material does not specify a complete configuration reference, HTTP deployment procedure, or approval UI. It also does not identify every supported MCP client beyond the environments named in the repository, which include Claude Desktop, Cursor, Windsurf, and VS Code. The read_file operation remains listed but is explicitly deprecated.

The project is source-available under the Business Source License 1.1. Review the repository license and policy behavior before deploying it in a production environment. The agentward-ai/agentward MCP server governs calls routed through its proxy; the supplied material does not claim that it automatically controls tools bypassing that proxy.

Read the full README β†’View source on GitHub β†’

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    Security gateway that wraps any MCP server with per-tool policies, approval gates, and optional Ed25519-signed receipts. Shadow mode logs every tool call; enforce mode blocks, rate-limits, or requires approval.

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Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks β€” not a rating.

GitHub stars
19
Stargazers on the source repository.
npm downloads
1.9M
Package downloads in the last 30 days.
Last commit
2mo ago
Most recent push to the default branch.
Install check
Inconclusive
Didn't respond in our test window β€” often a slow first install.
Tools exposed
14
Callable tools this server registers over MCP.
Directory activity
6 views
Config copies, upvotes, and views on AllMCPs.

Reviews

No reviews yet β€” be the first to share how this listing worked for you.

Frequently Asked Questions about Agentward

Use Python 3.11 or newer, run `pip install agentward`, and then run `agentward init`.

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Technical Specs & Signals

CategoryπŸ”’Security
PricingFree
More technical detailsExpand β–Ύ
TransportSTDIO
RuntimeNode.js
AuthNo auth required
LicenseBUSL-1.1
ClientsClaude Desktop, Cursor, Windsurf
Last updatedSep 21, 2026
Views6
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars19
GitHub Star CountTotal stargazers on GitHub representing community popularity (19 stars).
Last commit2mo ago
Last Repository CommitThe most recent commit or push recorded for this server's GitHub repository.Last commit on Jul 8, 2026
npm downloads1,945,615/mo
Monthly npm DownloadsAverage monthly package installs recorded from npm registry statistics.
63Quality signal: Good Β· 63/100How this signal is calculated β–Ύ
Server availabilityNot measured

Not scored for repo-hosted servers β€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership7/20
Documentation & tools30/30
Adoption & activity9/15
Community engagement1/10

A guidance signal from public completeness & health data β€” not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

Supply-chain signal

2 high-severity advisories on record for this package. Most advisories affect transitive dependencies and may not be exploitable in this server's actual usage β€” this is a directional signal, not a security audit.

Critical 0High 2Medium 0Low 0

Scanned 3d ago via OSV.dev Β· @modelcontextprotocol/server-filesystem (npm)

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