Massive Context MCP Server
massive-context-mcp
PyPI
v3.0.1
Published by egoughnour — no publish provenance, so origin is unverified, but the source is public: the repository link below is self-declared yet readable, so you can inspect the code before adopting it.
Handle 10M+ token contexts with chunking, sub-queries, and local Ollama inference
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 − 0 = 100. What the published surface and source actually contain:
The deterministic scan raised no scored threat in the surface it inspected — the threat score stayed at 100. Capability observations and advisory notes are recorded but never lower it.
2. Client adoption risk — 100 − 7 = 93. 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 |
| −1 | publisher verification (public source) — no provenance, but the source is public and inspectable |
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.
Findings 4
high Tool "rlm_exec" exposes command/code executionMTC-CAP-001
Tool "rlm_exec" appears to run shell commands or evaluate code (keyword "exec" 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 rlm_exec
high Dynamic code execution in server code (src/rlm_mcp_server.py)MTC-SRC-001
In the server's implementation (`src/rlm_mcp_server.py:1194`): Evaluating strings as code is the most direct RCE primitive; if any tool input reaches it, the server executes attacker-chosen code. This is read from the code itself — not from the tool description — so a poisoned server cannot hide it behind honest-looking metadata.
Evidence: ion, command injection, eval(), exec(), unsafe deserialization, hardcoded secrets, path traversal.", "code":
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 src/rlm_mcp_server.py
high Shell/command execution in server code (src/rlm_mcp_server.py)MTC-SRC-002
In the server's implementation (`src/rlm_mcp_server.py:300`): 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"), ("exec(", "Dynamic code execution"), ("__import__", "Dynamic module import"),
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 src/rlm_mcp_server.py
low Mutating tool "rlm_exec" declares no destructiveHintMTC-CAP-005
Tool "rlm_exec" 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 rlm_exec
Tools 17
Each tool and what it can reach — statically extracted from the published source.
rlm_execruns code / shellrlm_auto_analyzeno sensitive capabilityrlm_chunk_contextno sensitive capabilityrlm_filter_contextno sensitive capabilityrlm_firewall_statusno sensitive capabilityrlm_get_chunkno sensitive capabilityrlm_get_resultsno sensitive capabilityrlm_inspect_contextno sensitive capabilityrlm_list_contextsno sensitive capabilityrlm_load_contextno sensitive capability
Show 7 more tools ↓
rlm_ollama_statusno sensitive capabilityrlm_setup_ollamano sensitive capabilityrlm_setup_ollama_directno sensitive capabilityrlm_store_resultno sensitive capabilityrlm_sub_queryno sensitive capabilityrlm_sub_query_batchno sensitive capabilityrlm_system_checkno sensitive capability
What this scan could not see
- Tools were statically extracted from the published source (17 recovered), not enumerated from a running server. Tool-poisoning, Unicode-smuggling, capability and toxic-flow analysis ran on this inferred surface, but a mis-parsed registration could be missed or mis-attributed, so tool-derived findings are capped below “confirmed”. To grade the real runtime surface, scan the running server: --command "npx -y <package>".
Versions 1
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 |
|---|---|---|---|---|
v3.0.1 latest |
A 93/100 | 4 | 1.13.0 | 2026-08-25 |
Embed this score
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.
Verify this score yourself
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.
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