shadow-mcp
Local MCP server that inventories and risk-grades MCP servers configured on this machine.
What can you do with shadow-mcp?
- Discover (read-only) MCP servers from supported configuration and runtime sources:
- Inventory: merge sightings into one entry per logical server, even when a
- Risk-grade by delegating to the existing engines rather than
- Report: a ranked terminal table, a machine-readable JSON inventory, or
Install
Add this to your client's MCP configuration (Claude Desktop: claude_desktop_config.json; Cursor: .cursor/mcp.json; VS Code and others use the same "mcpServers" shape).
shadow-mcpclaude mcp add shadow-mcp -- uvx shadow-mcp==0.2.0 mcp-serve
{
"mcpServers": {
"shadow-mcp": {
"command": "uvx",
"args": [
"shadow-mcp==0.2.0",
"mcp-serve"
]
}
}
}
Documentation
From the project's README on GitHub, refreshed weekly. Links open on GitHub.
Contents
shadow-mcp
Discover and risk-grade the MCP servers actually present on this machine.
Most MCP security tooling assumes you already have a list of servers to audit.
On a real developer machine you don't: servers are scattered across Claude Code,
Codex, Claude Desktop, project-local .mcp.json files, DXT extensions, and live
processes that bind no port. shadow-mcp finds them first, then grades them.
This is the local-first answer to OWASP MCP09:2025 — Shadow MCP Servers.
What it does
discover -> inventory -> risk-grade -> report
- Discover (read-only) MCP servers from supported configuration and runtime sources:
Claude Code (
~/.claude.json, user + project scope),claude mcp list(catches remote + plugin servers no file contains), Codex (~/.codex/config.toml+ profiles), project.mcp.json, Claude Desktop config + DXT extension manifests, and the live process table. - Inventory: merge sightings into one entry per logical server, even when a
server appears under different names across hosts (
personal-opsvspersonal_ops), tracking every provenance. - Risk-grade by delegating to the existing engines rather than reimplementing them:
- Report: a ranked terminal table, a machine-readable JSON inventory, or markdown — plus a Shadow & attention section for the deltas that matter (running-but-unconfigured, broad blast radius, capable-but-ungraded).
The risk model and its OWASP mapping live in docs/risk-model.md.
Install
From this repository root, use uv:
make setup
The grading engines (mcp-audits and mcp-trust) are runtime dependencies
resolved from PyPI, not editable sibling checkouts or an engines group.
The installed mcp-trust package supplies its seed catalog; --registry-db or
SHADOW_MCP_MCPTRUST_DB selects an explicitly chosen local registry instead.
Use
uv run shadow-mcp scan # full pipeline, terminal report
uv run shadow-mcp scan --json out.json # machine-readable inventory
uv run shadow-mcp scan --format markdown # markdown report
uv run shadow-mcp discover # inventory only, no grading
uv run shadow-mcp sources # per-collector counts
uv run shadow-mcp grade-missing # A-F for servers the registry hasn't scanned
uv run shadow-mcp deep-scan cost-tracker # connect to a server, grade its real tools
Useful flags: --no-processes (skip the live process scan), --no-cli (skip
claude mcp list), --no-mcpaudit (inventory + mcp-trust only), --home PATH
(point discovery at a fixture tree).
Static vs connected grading
By default grading is static (config-only): no server is spawned, so grades reflect what's visible in the config. That's safe but coarse — a server's real capability only shows once you connect and list its tools.
shadow-mcp scan --connect (or deep-scan [names...]) spawns each stdio
server and enumerates its real tools, delegating to MCPAudit's connected engine
for a capability grade that actually differentiates (a filesystem server jumps
from a static A to a connected D). This is opt-in because connecting
executes the server; remote endpoints are never spawned (that's the network-scan
tier), and a server that needs real secrets to start falls back to its static
grade.
Development and safe verification
The committed uv.lock fixes the PyPI runtime and development graph. From the
repository root, run:
make check
The suite uses synthetic homes. Keep SHADOW_MCP_RUN_CONNECT unset: the
explicitly opted-in connected test is a separate server-execution lane. CI runs
the same aggregate gate on Python 3.11 through 3.15; see
the workflow. make build creates the wheel and
sdist used by the release workflow.
Do not use the normal scan, discover, sources, grade-missing or MCP tool
calls as a development smoke: they inventory the machine by default. CLI
deep-scan and scan --connect additionally execute servers. For changed JSON
or Markdown reports, check the corresponding fixture tests (tests/test_report.py)
and inspect synthetic output; this CLI has no browser UI. Actual workstation or
connected behavior requires its own explicitly authorized qualification.
Safety
- Read-only discovery. Collectors parse configs, invoke
claude mcp list(unless--no-cliis set), and list processes; nothing they find is ever mutated. (--connect/deep-scanis the one path that executes servers, and only when you explicitly ask.) - Secrets stay out. We record env variable names (to flag secret-bearing
servers per MCP01) but never their values. Inline credentials in command
arguments, URLs, and process parent commands are redacted before storage. A
captured inventory still contains local paths and hostnames, so treat
*.inventory.jsonas private (it is git-ignored by default).
Use as an MCP server
shadow-mcp can serve its own inventory tools as an MCP server so an agent can query your local MCP surface without leaving the conversation.
Tools
| Tool | Description |
|---|---|
scan_local | Full pipeline (discover → inventory → grade → report). Returns JSON. |
discover_local | Inventory every MCP server without grading. Returns JSON. |
deep_scan | Grade the named servers, or all servers when the list is empty (static, no spawning). Accepts names: list[str]. Returns JSON. |
list_sources | Per-collector source counts from a discover run. Returns JSON. |
Run the server
# directly from a local checkout
uv run shadow-mcp mcp-serve
# via uvx (once published to PyPI)
uvx shadow-mcp mcp-serve
LOCAL only. MCP tools read local configs and the process table, skip
claude mcp list, and never connect to hosted MCP endpoints or spawn servers.
Grading is static (config-based); connect=False is enforced unconditionally.
Scope
This is the local-first tool: it inventories one machine from its configs
and processes. A later network-scan expansion (probing hosts/ports for remote
MCP endpoints, org-wide fleet inventory, typosquat-distance provenance checks)
is deliberately out of scope here — see the bottom of docs/risk-model.md and
the project notes for what that would add.
Status
Stack
Python 3.11+; uv-managed locked dependencies; Ruff, mypy, and pytest checks; Hatchling wheel and sdist builds.
Known risks
- The minimum Python version remains 3.11 pending an owner decision about raising it to 3.12.
- The MCP tool name
deep_scanremains unchanged pending an owner decision; the similarly named CLI command can connect to servers. - Identity collisions in identity and inventory matching.
- Process sightings are deduplicated by name before owner classification.
- Grading evidence is limited to eight findings, and
criticalranks belowlow. - Collector failures can be silent.
--jsonis ignored bysourcesandgrade-missing.- Report writes are not atomic.
- Markdown and Rich output escaping differs.
- Dependency major upgrades, moving off Hatchling, a coverage threshold, package publishing, tags, and releases remain out of scope.
Next steps
Resolve the Python floor and MCP tool naming decisions, then address the listed behavior risks in a follow-up wave.
Frequently asked questions
What is shadow-mcp?
Local MCP server that inventories and risk-grades MCP servers configured on this machine.
How do I install shadow-mcp?
It runs on your machine. In Claude Code: claude mcp add shadow-mcp -- uvx shadow-mcp==0.2.0 mcp-serve. For other clients, paste the JSON configuration from this page into their MCP settings.
Does shadow-mcp need an API key?
Its registry entry lists no required key or secret. Some features may still need an account with the service it connects to.
Is shadow-mcp open source?
Its code is public on GitHub, but the repository does not declare a standard license.
Who maintains shadow-mcp?
It is published by saagpatel. AI.tn lists it but does not maintain or endorse it.
From the official MCP Registry. Listing is not an endorsement: review a server's code and permissions before giving it access to your data.