gcontext-mcp
PyPI
v0.3.3
Published by an unidentified publisher — no publish provenance and no public repository, so the publisher could not be verified and the source cannot be independently located.
gcontext connector — local MCP bridge: cloud structure, local secret values
The grade answers one question — how safe is this server for you to adopt — so it is computed in two auditable stages. Nothing below is an opinion or an LLM's guess; every line is a real term the deterministic engine applied, and the same input always yields the same number.
1. Threat score — 100 − 3.6 = 96. What the published surface and source actually contain:
| Points | What was found | Category |
|---|---|---|
| −3.6 | Near-miss of @upstash/context7-mcp MTC-SUP-005 | supply-chain |
2. Client adoption risk — 96 − 8 = 88. Three small, subtract-only factors that reflect your risk in adopting it — a clean scan proves less on a powerful, unverified or barely-inspectable package, so the grade says so plainly:
| Points | Adoption-risk factor |
|---|---|
| −6 | capability blast radius (high) — client exposure if the model is manipulated |
| −2 | publisher verification (unlinked) — no provenance/repo link, but the shipped source was fully read |
Capability observations and info notes are shown under Findings but never scored.
Open any row's finding below for the file, line and evidence behind a deduction.
Tools that read sensitive data ([tool_read_file]) and tools that can send data out ([tool_run_script, tool_run_shell]) are exposed together. An agent can move private data to the sink.
Evidence: sources [tool_read_file] → sinks [tool_run_script, tool_run_shell]
Fix: Keep secret-reading and egress capabilities on separate, separately-approved servers.
Location: flow tool_read_file → tool_run_script
Tool "tool_run_script" appears to run shell commands or evaluate code (keyword "run_script" in tool name). Arbitrary execution driven by model input is one of the most dangerous MCP capabilities; combined with any untrusted input it becomes RCE.
Fix: Sandbox execution, allowlist commands/arguments, and never pass model output to a shell unescaped.
Location: tool tool_run_script
Tool "tool_run_shell" appears to run shell commands or evaluate code (keyword "shell" in tool name). Arbitrary execution driven by model input is one of the most dangerous MCP capabilities; combined with any untrusted input it becomes RCE.
Fix: Sandbox execution, allowlist commands/arguments, and never pass model output to a shell unescaped.
Location: tool tool_run_shell
In the server's implementation (`server.py:179`): Spawning a shell/process is command-execution capability; with unsanitized tool input it is command injection / RCE. This is read from the code itself — not from the tool description — so a poisoned server cannot hide it behind honest-looking metadata.
Evidence: _sec(*args): return subprocess.run([_SECURITY, *args], capture_output=True, text=True) def _sec_read(name): """
Fix: Review this call path: confirm it never receives unsanitized tool input, constrain it, or remove it. Treat a server whose code reaches these sinks as high-capability regardless of what its tools claim.
Location: server server.py
Tool "tool_write_file" can write, overwrite or delete files (keyword "write_file" in tool name). Verify it is scoped to a safe directory.
Fix: Constrain file operations to an explicit, non-sensitive root; reject path traversal.
Location: tool tool_write_file
"gcontext-mcp" is edit-distance 2 from the high-traffic package "@upstash/context7-mcp". Verify this is the intended package.
Fix: Confirm you meant "@upstash/context7-mcp". Install packages only from their documented, official name.
Location: package gcontext-mcp
Tool "tool_write_file" can mutate/egress but declares no destructiveHint. Clients that don't default to spec-safe behavior may not prompt before running it.
Fix: Declare accurate annotations, and gate destructive tools on user confirmation regardless.
Location: tool tool_write_file
Tool "tool_run_script" can mutate/egress but declares no destructiveHint. Clients that don't default to spec-safe behavior may not prompt before running it.
Fix: Declare accurate annotations, and gate destructive tools on user confirmation regardless.
Location: tool tool_run_script
Tool "tool_run_shell" can mutate/egress but declares no destructiveHint. Clients that don't default to spec-safe behavior may not prompt before running it.
Fix: Declare accurate annotations, and gate destructive tools on user confirmation regardless.
Location: tool tool_run_shell
In a packaging/dev/install script (shipped, but not the server runtime) (`tests/test_journey.py:38`): Spawning a shell/process is command-execution capability; with unsanitized tool input it is command injection / RCE. This is read from the code itself — not from the tool description — so a poisoned server cannot hide it behind honest-looking metadata.
Evidence: ON_SECRET": ""} cloud = subprocess.Popen(["uv", "run", "--group", "dev", "python", "cloud_api.py"],
Fix: Review this call path: confirm it never receives unsanitized tool input, constrain it, or remove it. Treat a server whose code reaches these sinks as high-capability regardless of what its tools claim.
Location: server tests/test_journey.py
Each tool and what it can reach — statically extracted from the published source.
tool_read_filereads sensitive datatool_run_scriptruns code / shelltool_run_shellruns code / shelltool_write_filewrites filestool_deleteno sensitive capabilitytool_globno sensitive capabilitytool_grepno sensitive capabilitytool_list_dirno sensitive capabilitytool_overviewno sensitive capabilitytool_read_manyno sensitive capabilitytool_secretsno sensitive capabilitytool_setup_secretsno sensitive capabilityCross-tool combinations that form a data-exfiltration primitive (untrusted input → sensitive source → external sink).
Scan history per published version. The engine is deterministic — the same version always yields the same score, so a changed score means the package itself changed.
| Version | Score | Findings | Engine | Scanned |
|---|---|---|---|---|
v0.3.3 latest |
B 88/100 | 10 | 1.13.0 | 2026-08-25 |
Show this server's live Trust Score in your README, docs or website. The badge is served straight from the registry and updates automatically after every rescan — no API key needed. It links back to this page, so anyone who sees the grade can also read the findings behind it instead of taking a number on faith.
The score above is reproducible: the same package version always yields the same result. Run it locally or over the free API — no account, no LLM, fully deterministic.
npx mcptrustchecker scan gcontext-mcp --online --registry pypi
The Stripe Agent Toolkit enables popular agent frameworks including LangChain and Vercel's AI SDK to integrate with Stripe APIs through function calling.
MCP (Model Context Protocol) server for AgentGate. Enables Claude and other MCP-compatible AI assistants to request approvals.
Scan any website for AI agent readiness, payment protocols, and discovery endpoints
MCP server for aigently security guardrails — reads static catalog-data JSON, zero API dependency
Governed threat modeling, code threat verification, traceability & compliance, as MCP tools.
Governed threat modeling, code threat verification, traceability & compliance, as MCP tools.