Nia vs Context7: A Technical Comparison

Context7 by Upstash is a popular MCP server that brings library documentation into coding agents. It’s a solid tool for what it does. But when you compare architectures, Nia operates on a fundamentally different level.

The benchmark tells the story: Nia Oracle achieves 52.1% hallucination rate vs Context7’s 63.4%—an 11.3 percentage point improvement on bleeding-edge features.

Here’s why.

Architecture: Search vs Index

Context7 is a documentation search tool with 2 primary functions:

resolve-library-id → get-context

You search their pre-indexed library database, get a library ID, then fetch documentation snippets. That’s the entire API surface.

Nia is a context layer with 15+ specialized tools:

search — semantic search across your indexed sources
nia_grep — regex pattern matching in code
nia_read — read specific files with line numbers
nia_explore — browse repository file structures
nia_research — autonomous research (quick, deep, oracle modes)
context — save/share findings across sessions and agents
nia_package_search_hybrid — AI-powered search across 3,000+ packages
index — add any repo, docs site, paper, or local folder

Context7 searches a fixed library index. Nia lets you build your own knowledge base.

You Control What Gets Indexed

Context7 maintains a curated library database. You query it and hope your library exists.

Nia lets you index anything:

Source Type	Context7	Nia
Public library docs	✓	✓
GitHub repositories	✗	✓
Private repos	✗ (Pro only, extra cost)	✓
Research papers (arXiv)	✗	✓
Local folders	✗	✓
iMessage/Telegram/browser history	✗	✓
Any documentation site	✗	✓

When a library ships a breaking change, you don’t wait for someone to update Context7’s index. You re-index the source yourself and get immediate, correct context.

The Benchmark: Bleeding-Edge Features

We tested both tools on newly released and beta features—the exact scenario where LLMs fail because features shipped after training cutoff.

Tool	Hallucination Rate
Nia Oracle	52.1%
Context7	63.4%
Exa Code	65.2%
Brave Search	66.7%
no-RAG	81.0%
GPT-5 Web	89.6%
GPT-5 (baseline)	95.5%

Methodology: Claude 4.5 Sonnet and GPT-5 with temperature=0.0. Custom HallucinationClassifier evaluated code only against documentation, ignoring the judge’s training data. Error categories: invented_method, wrong_parameter, outdated_api.

Nia’s 11.3% improvement over Context7 comes from deeper source indexing—we don’t just surface snippets, we index the actual SDK source code.

Oracle Research: No Equivalent in Context7

Nia’s Oracle is an autonomous research agent that:

Searches the web to discover relevant sources
Automatically indexes them
Searches across indexed code and docs
Synthesizes findings with full citations

# Nia Oracle
nia_research(
    query="How does authentication work in FastAPI?",
    mode="oracle",
    repositories=["fastapi/fastapi"],
    output_format="markdown with code examples"
)

Context7 has no equivalent. You manually search their library index, get snippets, and synthesize yourself.

For complex questions that span multiple sources or require discovering new repositories, Oracle handles the entire workflow autonomously.

Context7 is stateless. Every query starts fresh.

Nia maintains context across sessions and agents:

# Save findings in Cursor
context(action='save',
        title='FastAPI auth implementation',
        content='Analysis of JWT flow in FastAPI...',
        agent_source='cursor')

# Retrieve in Claude Code
context(action='retrieve', context_id='...')

This enables workflows where you plan in one agent and execute in another. Research in Cursor, implement in Claude Code. All context transfers.

Beyond Code: Use Cases Context7 Can’t Handle

Context7 indexes libraries. Nia indexes anything. Users have built:

Cursor Forum search — find answers to Cursor-specific issues
Paul Graham essay search — build writing assistants grounded in his thinking
Legal document search — index PDFs from specific jurisdictions
Healthcare documentation — domain-specific medical agents
Private wiki search — onboarding agents for internal company docs
Epstein archive search — document analysis applications

The /explore page at trynia.ai shows community-contributed sources across domains.

Local Sync: Your Private Knowledge Base

Nia Sync is a daemon that continuously syncs local data:

nia add ~/Documents/notes
nia add ~/Library/Messages/chat.db  # iMessage
nia start

Your local folders, chat history, and databases become searchable. Private to your account, never mixed with public sources.

Context7 has nothing comparable.

Pricing Comparison

	Context7 Free	Context7 Pro	Nia Free	Nia Pro
Price	$0	$10/seat/mo	$0	$15/mo
API Calls	500/mo	1000/seat	50/mo	1000/mo
Private Repos	✗	$15/1M tokens	✗	Included
Research Agent	✗	✗	✗	30/mo
Oracle	✗	✗	✗	30/mo
Context Sharing	✗	✗	5	100
Package Search	✗	✗	50/mo	Unlimited

Context7 charges extra for private repository parsing. Nia includes it in the base price.

When to Use Each

Use Context7 if:

You only need public library documentation
Simple snippet retrieval is sufficient
You don’t need cross-session context

Use Nia if:

You need to index specific sources (private repos, internal docs, papers)
You want autonomous research across multiple sources
You need context to persist across agents and sessions
You’re building applications beyond library documentation
You want lower hallucination rates on bleeding-edge features

Conclusion

Context7 is a documentation search tool. Nia is a context layer.

The 11.3% improvement in hallucination rates isn’t accidental—it comes from architectural differences. Indexing source code directly, providing 15+ specialized tools, enabling cross-session context, and supporting autonomous research all contribute to more accurate agent outputs.

For teams building serious agent applications that require reliable context beyond public library docs, Nia’s approach wins.

Try Nia at trynia.ai.