api-agent

Provides a universal MCP server that exposes GraphQL and REST APIs as MCP tools. It introspects a target GraphQL endpoint or OpenAPI/Swagger spec, answers questions in natural language, fetches data, stores results in DuckDB, and performs SQL post-processing. It also supports “recipe learning” to cache reusable query pipelines as additional dynamic MCP tools.

Evaluated Mar 30, 2026 (21d ago)
Repo ↗ DevTools mcp api-integration graphql rest duckdb sql agents openapi observability python
⚙ Agent Friendliness
60
/ 100
Can an agent use this?
🔒 Security
54
/ 100
Is it safe for agents?
⚡ Reliability
26
/ 100
Does it work consistently?

Score Breakdown

⚙ Agent Friendliness

MCP Quality
85
Documentation
78
Error Messages
0
Auth Simplicity
70
Rate Limits
20

🔒 Security

TLS Enforcement
70
Auth Strength
55
Scope Granularity
35
Dep. Hygiene
45
Secret Handling
60

TLS enforcement is not explicitly stated; examples use localhost HTTP for the MCP server. Downstream API auth is passed via X-Target-Headers (static headers) which is flexible but can be risky if logged or mishandled by clients/servers. The tool set is read-only by default with an explicit unsafe-path allowlist for write operations, which is a good control, but scope granularity for authorization is not described. No security posture details (logging redaction, secret handling practices, SSRF protections, path/path-matching safety beyond glob patterns) are provided in the README content.

⚡ Reliability

Uptime/SLA
0
Version Stability
40
Breaking Changes
30
Error Recovery
35
AF Security Reliability

Best When

You want an agent/MCP client to explore and analyze external GraphQL/REST APIs quickly using a consistent tool interface, and you accept that results may involve SQL post-processing over fetched data.

Avoid When

You need deterministic, contract-first correctness (e.g., strict schema-to-query validation) or you must minimize data retention/storage, or you cannot safely supply auth headers to a server that will call third-party endpoints.

Use Cases

  • Natural-language querying over unfamiliar GraphQL/REST APIs
  • Post-processing API data with SQL (ranking, filtering, joins, aggregations) even if the upstream API lacks those capabilities
  • Rapid creation of MCP tools over many APIs without writing custom glue code
  • Read-only API exploration and analytics; optionally controlled unsafe operations via allowlisting
  • Reusing successful query patterns via cached recipes

Not For

  • Production workloads requiring strict data governance unless additional controls are added
  • APIs that require complex authentication flows not representable via static headers
  • Environments that cannot tolerate storing fetched data in DuckDB
  • Use cases requiring guaranteed pagination completeness from upstream APIs (unless explicitly handled)
  • Use cases needing strong, audited mutation semantics (mutations only “blocked unless explicitly allowed”)

Interface

REST API
No
GraphQL
No
gRPC
No
MCP Server
Yes
SDK
No
Webhooks
No

Authentication

Methods: Environment variable for LLM provider: OPENAI_API_KEY (and optional OPENAI_BASE_URL) Target API auth via MCP client headers: X-Target-Headers (static JSON headers such as Authorization: Bearer …)
OAuth: No Scopes: No

The README describes passing downstream API authentication as static HTTP headers (X-Target-Headers). It also notes read-only-by-default behavior and an unsafe method allowlist controlled by X-Allow-Unsafe-Paths.

Pricing

Model: OpenAI model (default stated as gpt-5.2); cost dep
Free tier: No
Requires CC: No

No pricing for the server itself is stated in the provided content; it appears to rely on OpenAI API usage plus your infrastructure/runtime.

Agent Metadata

Pagination
unknown
Idempotent
False
Retry Guidance
Not documented

Known Gotchas

  • Rate limits and pagination behavior of the upstream API are not described in the provided content; agent may fetch partial data unless the upstream API/data volume is handled explicitly.
  • Auth is provided via static headers; if tokens expire, long-running agents may fail without a refresh mechanism.
  • Results are stored in DuckDB; large responses may increase memory/disk usage and affect reliability.
  • Recipes depend on schema hash; schema changes can invalidate cached tools.

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Scores are editorial opinions as of 2026-03-30.

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