In-depth architectural comparison of the Gopher MCP and Enrichr MCP Server MCP servers. Compare execution transports, security boundaries, tool capabilities, quality scores, and ready-to-paste client installation snippets for Claude, Cursor, Windsurf, and VS Code.
At a Glance & Executive Verdict
Gopher MCP
Search & Data Extraction · Local stdio
Quality: 56/100 (Good) | Auth: No auth required
Enrichr MCP Server
Search & Data Extraction · Local stdio
Quality: 61/100 (Good) | Auth: No auth required
Verdict Summary: Choose Gopher MCP if you need specialized Search & Data Extraction tools running via a local process. Choose Enrichr MCP Server if your workspace requires Search & Data Extraction integration with local subprocess execution. Both servers can be configured concurrently in your client's mcpServers manifest.
Which MCP Server Should You Choose?
Choose Gopher MCP when:
You need dedicated capabilities in the Search & Data Extraction domain.
You prefer local stdio subprocess transport architecture.
Your security boundary fits: No auth required (Free / Open Source).
You have access to required keys: GOPHER_MAX_RESPONSE_SIZE, GOPHER_TIMEOUT_SECONDS.
Primary tools included: Dual protocol support for Gopher and Gemini, TLS encryption with TOFU certificate validation, Structured JSON output optimized for LLMs.
Modern, cross-platform MCP server enabling AI assistants to browse and interact with both Gopher protocol and Gemini protocol resources safely and efficiently. Features dual protocol support, TLS security, and structured content extraction.
A MCP server that provides gene set enrichment analysis using the Enrichr API
Category & Scope
Tools & Capabilities Breakdown
Gopher MCP Tools (6)
Dual protocol support for Gopher and Gemini
TLS encryption with TOFU certificate validation
Structured JSON output optimized for LLMs
Built-in timeouts, size limits, and input sanitization
Cross-platform support on Windows, macOS, and Linux
Async/await architecture with intelligent caching
Enrichr MCP Server Tools (2)
enrichr_analysis
Ready-to-Paste Client Configurations
Paste either (or both) of these JSON server blocks into your client config file (e.g. claude_desktop_config.json or ~/.cursor/mcp.json).
Gopher MCP is categorized under Search & Data Extraction and uses a local stdio subprocess. In contrast, Enrichr MCP Server belongs to Search & Data Extraction using local stdio subprocess. Select Gopher MCP when you need capabilities focused on search & data extraction and Enrichr MCP Server when you require tools for search & data extraction.
Perform gene set enrichment analysis using Enrichr across multiple gene set libraries. Returns only statistically significant terms (adjusted p < 0.05).
Configured default libraries:
- GO_Biological_Process_2026: Current Gene Ontology biological process terms — biological objectives and programs accomplished by gene products. The default choice for GO biological process enrichment.
- KEGG_2026: Current KEGG metabolic and signaling pathways — the up-to-date KEGG release; prefer over older KEGG vintages.
- Reactome_Pathways_2024: Current Reactome release — curated, peer-reviewed pathways for signaling, metabolism, gene expression, and disease.
- MSigDB_Hallmark_2020: Hallmark gene sets representing well-defined biological states and processes from MSigDB.
- ChEA_2022: ChIP-seq experiments from GEO, ENCODE, and publications identifying transcription factor-gene interactions from human and mouse.
- GWAS_Catalog_2025: Current genome-wide association study results from the NHGRI-EBI GWAS Catalog, linking genes to human traits and diseases.
- Human_Phenotype_Ontology: Standardized vocabulary of phenotypic abnormalities associated with human diseases.
- PPI_Hub_Proteins: Highly connected hub proteins from protein-protein interaction networks.
- DGIdb_Drug_Targets_2024: Drug-gene interactions from the Drug Gene Interaction Database — druggable targets and their compounds.
- CellMarker_2024: Manually curated cell type markers from CellMarker database for human and mouse.
Any library in Enrichr's live catalog is accepted. Enrichr adds and retires
libraries continuously, so do not rely on a memorized list: call
suggest_libraries, or read the enrichr://libraries resource, to discover the
libraries that currently exist.
Pass 'background' to test against a custom background gene set (for example,
only the genes expressed in your assay) instead of Enrichr's whole-genome
default. This is the statistically correct choice whenever the gene list was
drawn from a restricted universe, and it matters: the whole-genome default can
overstate significance by many orders of magnitude.
Each library's result reports 'backgroundCorrected'. If Enrichr's background
service is unavailable the result falls back to uncorrected whole-genome
p-values, flagged with a warning — treat those numbers as inflated and re-run
rather than reporting them as background-corrected.
suggest_libraries
Suggest relevant Enrichr libraries for a research question. Use this before enrichr_analysis to pick the best libraries for a specific topic.