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Postgres MCP Pro

MCP server giving agents safe PostgreSQL access plus index tuning, execution-plan analysis, and database health checks.

@ai-supply
Instalaciones1.3k
⟳ upstream v0.3.0 · updated 1y ago
↗ Repositorio fuente
← More Data & ETLData & ETL leaderboard →How we grade security →Source ↗
! Grade B · 75/100 · ReviewSecurity assessment
✓No compromise signals10capabilities surfaced1known CVE8of 20 OWASP controls clear
Suspicious code patternsSuspicious code patternsInternal host / private infrastructure referencePotentially unbounded loop
scanned 1mo ago·osv · gitleaks · opengrep · picklescan + heuristics·full breakdown in the Security tab ↓

Postgres MCP Pro

Postgres MCP Pro is a Model Context Protocol server that gives AI agents deep, guarded access to PostgreSQL. It goes beyond plain query execution: agents can inspect schemas, run configurable read-only or read/write SQL, diagnose slow queries, and get principled index recommendations backed by the query planner.

Key features

  • Configurable access modes: unrestricted for local development, restricted read-only for production safety
  • Index tuning that simulates hypothetical indexes and reports the estimated plan-cost change
  • Database health checks covering bloat, cache hit rates, vacuum status, and connection saturation
  • EXPLAIN/EXPLAIN ANALYZE plan inspection so agents can reason about and optimize queries
  • Works with any Postgres 13+ instance over a standard connection string, local or managed
  • Ships as a container and via pip/uvx for drop-in wiring into MCP clients

It is a practical bridge for coding agents that need to understand a real database's structure and performance rather than blindly issuing SQL.

Curated mirror of the open-source Postgres MCP Pro (MIT). Get it from the source.

Rating rank
#1
of 24 in Data & ETL
Install rank
#23
of 24 in Data & ETL
Security score
75/100 · B
review
Security rank
#10
of 24 in Data & ETL
Installs
1.3k
cat avg 164k
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! Security: Review · 7575/100 · grade Bscanned 1mo ago
✓ no compromise signals11 risk-surface · 7/20 OWASP controls flagged

Compromise signals — malicious or tampered code (leaked secrets, backdoors, a dropped executable) — reduce the score, and known dependency CVEs carry a bounded penalty (they warrant review but never QUARANTINE — update the dependency to clear). Other dangerous-by-capability traits are risk surface, expected for some capabilities. Every finding is mapped to its OWASP control below.

What this capability can do · med confidence (static)
⚑ filesystem⚑ network⚑ secrets
egress → www.crystaldba.ai, img.shields.io, pypi.org, discord.gg, x.com, modelcontextprotocol.io, www.pgadmin.org, docs.astral.sh +18
auth: api_keyimg.shields.ioopensource.orgpypi.orgdiscord.ggx.comgithub.commodelcontextprotocol.iowww.crystaldba.ai

Findings mapped to the OWASP Top 10 for LLM Applications (2025) and the OWASP Machine Learning Security Top 10. Expand any flagged control for the exact findings — compromise reduces the score; expected/risk-surface do not, except a known CVE, which carries a small bounded penalty (high/critical → Review).

OWASP Top 10 for LLM Applications
⚠LLM03Supply Chaincritical
Vulnerable/compromised dependencies, models or archives in the artifact.
•Vulnerable dependencies — 103 known vulnerabilities in: aiohttp@3.11.16, cryptography@46.0.3, diskcache@5.6.3, h11@0.14.0, idna@3.10, pygments@2.19.1, pyjwt@2.10.1, pytest@9.0.2 (CWE-1395)known CVE · -25 pts
⚠LLM05Improper Output Handlinghigh
Code that pipes model/user output into shell, eval, SQL or paths unsafely.
•Suspicious code patterns — destructive rm -rf / · crystaldba-postgres-mcp-07eb329/Dockerfile (CWE-78)risk surface
•Suspicious code patterns — pipe-to-shell install · crystaldba-postgres-mcp-07eb329/README.md (CWE-494)risk surface
•Suspicious code patterns — dynamic code execution · crystaldba-postgres-mcp-07eb329/tests/unit/index/test_dta_calc.py (CWE-95)risk surface
⚠LLM06Excessive Agencymedium
Over-broad tool/permission surface or unrestricted egress.
•External endpoints declared — 3 distinct host(s) · crystaldba-postgres-mcp-07eb329/.gitignoreexpected
•External endpoints declared — 2 distinct host(s) · crystaldba-postgres-mcp-07eb329/Dockerfileexpected
•External endpoints declared — 25 distinct host(s) · crystaldba-postgres-mcp-07eb329/README.mdexpected
•External endpoints declared — 1 distinct host(s) · crystaldba-postgres-mcp-07eb329/devenv.nixexpected
•External endpoints declared — 4 distinct host(s) · crystaldba-postgres-mcp-07eb329/examples/movie-app.mdexpected
⚠LLM07System Prompt Leakagemedium
Secrets, internal hosts or proprietary logic exposed in shipped prompts.
•Internal host / private infrastructure reference — shipped content references a private IP range or internal-only host · crystaldba-postgres-mcp-07eb329/README.md (CWE-200)risk surface
⚠LLM10Unbounded Consumptionmedium
Unbounded loops/recursion causing DoS or runaway cost.
Enforced at runtime by the gateway (rate limits + spend caps + size caps); static check flags unbounded loops.
•Potentially unbounded loop — an infinite loop (while True / while(1) / for(;;)) may cause runaway consumption · crystaldba-postgres-mcp-07eb329/src/postgres_mcp/index/dta_calc.py (CWE-835)risk surface
§LLM09MisinformationGovernance
Artifacts designed to produce false/deceptive output.
Detectable only by runtime behavioral evaluation; addressed via responsible-use attestation.
✓LLM01Prompt InjectionPassed
✓LLM02Sensitive Information DisclosurePassed
✓LLM04Data and Model PoisoningPassed
Backdoors/poisoning in training data or serialized models.
Behavioral poisoning needs model execution; static check covers unsafe serialization + dataset skew only.
✓LLM08Vector and Embedding WeaknessesPassed
PII or plaintext source leakage in embedding/vector exports.
Embedding inversion/poisoning is largely runtime; static check covers PII in vector exports.
OWASP Machine Learning Security Top 10
⚠ML06AI Supply Chaincritical
Compromised PyPI/npm packages, typosquats, unsafe serialized models.
•Vulnerable dependencies — 103 known vulnerabilities in: aiohttp@3.11.16, cryptography@46.0.3, diskcache@5.6.3, h11@0.14.0, idna@3.10, pygments@2.19.1, pyjwt@2.10.1, pytest@9.0.2 (CWE-1395)known CVE · -25 pts
⚠ML09Output Integrityhigh
Middleware tampering with model outputs in transit.
Gateway enforces TLS + response integrity; static check flags output-rewriting code.
•Suspicious code patterns — destructive rm -rf / · crystaldba-postgres-mcp-07eb329/Dockerfile (CWE-78)risk surface
•Suspicious code patterns — pipe-to-shell install · crystaldba-postgres-mcp-07eb329/README.md (CWE-494)risk surface
•Suspicious code patterns — dynamic code execution · crystaldba-postgres-mcp-07eb329/tests/unit/index/test_dta_calc.py (CWE-95)risk surface
§ML01Input Manipulation (Adversarial)Governance
Models vulnerable to adversarial perturbations.
Requires runtime robustness evaluation; addressed via publisher robustness attestation.
§ML03Model InversionGovernance
Training data reconstructable from a model's outputs.
Runtime/evaluation property; addressed via model-card data-provenance + DP attestation.
§ML04Membership InferenceGovernance
Determining whether a record was in the training set.
Runtime/evaluation property; addressed via overfitting disclosure + DP attestation.
§ML08Model SkewingGovernance
Models trained on skewed data producing biased output.
Requires fairness evaluation; addressed via model-card bias/limitations disclosure.
✓ML02Data PoisoningPassed
Poisoned training datasets with triggers or anomalous distributions.
Static check covers trigger phrasing, PII and label skew; full poisoning detection is runtime.
✓ML05Model TheftPassed
Unlicensed re-distribution / license-incompatible derivatives.
Static check verifies license declaration; extraction throttling is runtime.
✓ML07Transfer Learning AttackPassed
Backdoored base models / LoRA adapters propagating to derivatives.
Backdoor detection needs behavioral probing; static check covers unsafe serialization + provenance.
✓ML10Model Poisoning (Weights)Passed
Tampered model weight files; integrity must be verifiable.
Static check enforces safe formats + records a content hash for downstream verification.
Other findings (5) · hygiene / uncategorized
•Unrecognized file type — '.gitignore' is not on the allowlist · crystaldba-postgres-mcp-07eb329/.gitignorerisk surface
•Unrecognized file type — '.python-version' is not on the allowlist · crystaldba-postgres-mcp-07eb329/.python-versionrisk surface
•Unrecognized file type — '.?' is not on the allowlist · crystaldba-postgres-mcp-07eb329/Dockerfilerisk surface
•Unrecognized file type — '.nix' is not on the allowlist · crystaldba-postgres-mcp-07eb329/devenv.nixrisk surface
•Unrecognized file type — '.postgres-hypopg' is not on the allowlist · crystaldba-postgres-mcp-07eb329/tests/Dockerfile.postgres-hypopgrisk surface
✔ verified source · pinned crystaldba-postgres-mcp-07eb329
Check against a policy

The same gate an agent runs before installing (POST /api/v1/trust/postgres-mcp-pro/check). Click a policy:

Consume Postgres MCP Pro programmatically. Authenticate with an API key or session — see Authorize an agent.

# Agents: CHECK BEFORE YOU INSTALL (no auth) — score, grade, level, capability manifest
curl https://ai-supply.store/api/v1/trust/postgres-mcp-pro

# Gate against your org policy (returns { pass, violations })
curl -X POST https://ai-supply.store/api/v1/trust/postgres-mcp-pro/check \
  -H "Content-Type: application/json" \
  -d '{"minGrade":"B","denyPermissions":["shell"],"denyUnknownEgress":true}'

# CLI
npx ai-supply add postgres-mcp-pro

# REST (install → download)
curl -X POST https://ai-supply.store/api/v1/listings/postgres-mcp-pro/install \
  -H "Authorization: Bearer $AIM_KEY"

# MCP tool
install_listing({ "slug": "postgres-mcp-pro" })
OpenAPI spec →
vlatest
! Security: Review · 751mo ago

Curated mirror — latest upstream source. See the repository for tagged releases.

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