csv-parser

Streaming CSV parser for Node.js with a rich feature set: async iterators, callbacks, pipe-friendly streams, and synchronous mode. Part of the node-csv suite (csv-parse, csv-generate, csv-transform, csv-stringify). Handles quoted fields, multiline records, custom delimiters, and encoding issues robustly.

Evaluated Mar 06, 2026 (0d ago) v3.x
Homepage ↗ Repo ↗ Developer Tools csv parsing streaming node.js data-pipeline etl
⚙ Agent Friendliness
68
/ 100
Can an agent use this?
🔒 Security
98
/ 100
Is it safe for agents?
⚡ Reliability
87
/ 100
Does it work consistently?

Score Breakdown

⚙ Agent Friendliness

MCP Quality
--
Documentation
88
Error Messages
82
Auth Simplicity
100
Rate Limits
100

🔒 Security

TLS Enforcement
100
Auth Strength
100
Scope Granularity
100
Dep. Hygiene
85
Secret Handling
100

Local library with no network calls. Main concern is CSV injection if output is used in spreadsheet formulas — sanitize output for downstream spreadsheet use.

⚡ Reliability

Uptime/SLA
100
Version Stability
85
Breaking Changes
78
Error Recovery
85
AF Security Reliability

Best When

You need robust, streaming CSV parsing in Node.js with fine-grained control over delimiters, quoting, encoding, and error handling.

Avoid When

You need browser-side parsing or Excel format support — use PapaParse for browser or exceljs for spreadsheets.

Use Cases

  • Parse large CSV files as Node.js streams without loading the full file into memory for agent ETL pipelines
  • Convert CSV uploads to JSON objects for downstream processing in data ingestion agents
  • Stream CSV records through async iterators for row-by-row processing in agent pipelines
  • Handle malformed or irregular CSV data with configurable relaxed parsing modes
  • Parse TSV, PSV, and other delimiter-separated files with custom delimiter configuration

Not For

  • Browser-side CSV parsing — PapaParse is better for browser environments with web worker support
  • Excel/XLSX file parsing — use xlsx or exceljs for spreadsheet format support
  • Extremely high-performance batch CSV ingestion — consider DuckDB or Apache Arrow for analytics-scale parsing

Interface

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

Authentication

Methods: none
OAuth: No Scopes: No

Local library — no authentication required.

Pricing

Model: open_source
Free tier: Yes
Requires CC: No

MIT license. Part of the node-csv monorepo maintained by Adaltas.

Agent Metadata

Pagination
none
Idempotent
Full
Retry Guidance
Not documented

Known Gotchas

  • Streaming mode processes records as they arrive — agents must handle backpressure and use async iterators or pipe correctly to avoid memory buildup
  • columns: true option maps headers automatically but header row must exist — always verify CSV structure before enabling
  • BOM (byte order mark) in UTF-8 files causes spurious first-field values — use bom: true option to strip automatically
  • relax_quotes and relax_column_count options are needed for real-world CSV that violates strict RFC 4180 — enable for user-generated data
  • Synchronous parse() is convenient but loads entire file into memory — always use streaming API for files > 50MB
  • csv-parse v5+ changed to ES module syntax — agents using CommonJS require() need to use dynamic import() or pin to v4

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Scores are editorial opinions as of 2026-03-06.

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