Qiskit Mcp Servers MCP Server
qiskit-mcp-servers
PyPI
v0.12.0
Published by qiskit — 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.
Model Context Protocol servers for IBM Quantum services and Qiskit
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 1
high Shell/command execution in server code (qiskit-gym-mcp-server/src/qiskit_gym_mcp_server/server_tools.py)MTC-SRC-002
In the server's implementation (`qiskit-gym-mcp-server/src/qiskit_gym_mcp_server/server_tools.py:476`): 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: _tb_state.process = subprocess.Popen( # nosec B603 B607 ["tensorboard", "--logdir", QISKIT_GYM_TENSORBO
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 qiskit-gym-mcp-server/src/qiskit_gym_mcp_server/server_tools.py
Tools 71
Each tool and what it can reach — statically extracted from the published source.
get_environment_info_toolreads sensitive dataget_page_toolingests untrusted inputactive_account_info_toolno sensitive capabilityactive_instance_info_toolno sensitive capabilityai_clifford_synthesis_toolno sensitive capabilityai_linear_function_synthesis_toolno sensitive capabilityai_pauli_network_synthesis_toolno sensitive capabilityai_permutation_synthesis_toolno sensitive capabilityai_routing_toolno sensitive capabilityanalyze_circuit_toolno sensitive capability
Show 61 more tools ↓
available_instances_toolno sensitive capabilitybatch_train_environments_toolno sensitive capabilitycancel_job_toolno sensitive capabilitycompare_optimization_levels_toolno sensitive capabilityconvert_qasm3_to_qpy_toolno sensitive capabilityconvert_qpy_to_qasm3_toolno sensitive capabilitycreate_clifford_env_toolno sensitive capabilitycreate_coupling_map_toolno sensitive capabilitycreate_linear_function_env_toolno sensitive capabilitycreate_permutation_env_toolno sensitive capabilitydelete_environment_toolno sensitive capabilitydelete_model_toolno sensitive capabilitydelete_saved_account_toolno sensitive capabilityexport_circuit_to_qasm_toolno sensitive capabilityextract_subtopologies_toolno sensitive capabilityfind_optimal_qubit_chains_toolno sensitive capabilityfind_optimal_qv_qubits_toolno sensitive capabilitygenerate_random_clifford_toolno sensitive capabilitygenerate_random_linear_function_toolno sensitive capabilitygenerate_random_permutation_toolno sensitive capabilityget_backend_calibration_toolno sensitive capabilityget_backend_properties_toolno sensitive capabilityget_coupling_map_toolno sensitive capabilityget_fake_backend_coupling_map_toolno sensitive capabilityget_job_results_toolno sensitive capabilityget_job_status_toolno sensitive capabilityget_model_info_toolno sensitive capabilityget_tensorboard_metrics_toolno sensitive capabilityget_tensorboard_status_toolno sensitive capabilityget_training_metrics_toolno sensitive capabilityget_training_status_toolno sensitive capabilityhybrid_ai_transpile_toolno sensitive capabilityleast_busy_backend_toolno sensitive capabilitylist_available_fake_backends_toolno sensitive capabilitylist_backends_toolno sensitive capabilitylist_environments_toolno sensitive capabilitylist_loaded_models_toolno sensitive capabilitylist_my_jobs_toolno sensitive capabilitylist_saved_accounts_toolno sensitive capabilitylist_saved_models_toolno sensitive capabilitylist_subtopology_shapes_toolno sensitive capabilitylist_tensorboard_experiments_toolno sensitive capabilitylist_training_sessions_toolno sensitive capabilityload_circuit_from_qasm_toolno sensitive capabilityload_model_toolno sensitive capabilitylookup_error_code_toolno sensitive capabilityrun_estimator_toolno sensitive capabilityrun_sampler_toolno sensitive capabilitysave_model_toolno sensitive capabilitysearch_docs_toolno sensitive capabilitysetup_ibm_quantum_account_toolno sensitive capabilitystart_tensorboard_toolno sensitive capabilitystart_training_toolno sensitive capabilitystop_tensorboard_toolno sensitive capabilitystop_training_toolno sensitive capabilitysynthesize_clifford_toolno sensitive capabilitysynthesize_linear_function_toolno sensitive capabilitysynthesize_permutation_toolno sensitive capabilitytranspile_circuit_toolno sensitive capabilityusage_info_toolno sensitive capabilitywait_for_training_toolno sensitive capability
What this scan could not see
- Tools were statically extracted from the published source (71 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 |
|---|---|---|---|---|
v0.12.0 latest |
A 93/100 | 1 | 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.
npx mcptrustchecker scan qiskit-mcp-servers --online --registry pypiMore in API Development
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