Codebase Memory MCP vs Stata MCP
A side-by-side look at the Codebase Memory MCP and Stata MCP MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
Verdict: choose Codebase Memory MCP for knowledge & memory work as a local process; choose Stata MCP for data science tools as a local process. You can also run both side by side in one mcpServers block.
Which MCP server should you choose?
Choose Codebase Memory MCP when
- You need dedicated capabilities in the Knowledge & Memory domain.
- You prefer a local stdio subprocess transport.
- Its auth model fits you: No auth required.
- You want tools like
index_repository, search_graph, query_graph.
Choose Stata MCP when
- You need dedicated capabilities in the Data Science Tools domain.
- You prefer a local stdio subprocess transport.
- Its auth model fits you: No auth required.
- You want tools like
stata_do, get_data_info, help.
Feature & specification comparison
Rows where the two servers differ are marked.
| Spec | ||
|---|---|---|
| Category | Knowledge & Memory | Data Science Tools |
| Quality signal | 73/100 · Great | 57/100 · Good |
| Install command | Confirmed | Confirmed |
| Transport | Local subprocess (stdio) | Local subprocess (stdio) |
| Auth | No auth required | No auth required |
| Pricing | Free | Free |
| Required env vars | None listed | None listed |
| Verified owner | Community listing | Community listing |
| GitHub stars | 47,004 | 267 |
| Directory activity | 8 views 1 installs 1 upvotes | 7 views 0 installs 0 upvotes |
| Tools | 17 | 4 |
| Full listing | View Codebase Memory MCP | View Stata MCP |
Tools & capabilities
Codebase Memory MCP tools 17
index_repositoryIndex a repository. full/moderate add semantics; fast omits them; cross-repo-intelligence links services. Reports coverage gaps.search_graphFind symbols via BM25 query, regex name/qn filters, or semantic_query. Rows keep qn/file/lines and in/out over CALLS/USAGE/CALL_REFERENCE/INHERITS/IMPLEMENTS.query_graphRead-only Cypher for multi-hop, aggregation, complexity, or cross-service analysis. Default: 200 visible rows with exact/lower-bound totals and truncation; continue safely with next_cursor. graph=missed is a file tree of flagged coverage gaps; absence is not proof of completeness. Use get_graph_schema(diagnostics=full) for properties.trace_pathTrace callers/callees, data flow, or cross-service paths. Defaults exclude tests and resolver evidence. Rows keep qn/hop with explicit totals, relations, and continuations.get_code_snippetRead a search_graph symbol. auto bounds source and outlines large containers; full restores up to 500 lines. Source/outline pages continue; coverage_note marks gaps.get_file_outlineDeclaration outline of one exact repository-relative file: optional exact label filter, source order, exact total/offset/limit paging; file/folder/container nodes excluded.get_graph_schemaGet node-label and edge-type counts. diagnostics=full also lists queryable properties.compare_graphsCompare two indexed snapshots: deterministic target-only additions and base-only removals of stable node/edge identities; each set capped by limit and a 512 KiB budget with exact totals and truncation reasons.get_architectureCompact counts, languages, packages, entry points. Request structure, dependencies, routes, hotspots, boundaries, layers, clusters, cycles, or file_tree; path scopes a directory.search_codeGraph-ranked text search: compact symbols, full bounded source, or file paths.list_projectsList projects with stable paging. Identity is lean; stats adds graph sizes.delete_projectDelete a project from the index- +5 more on the listing page
Stata MCP tools 4
stata_doExecute a Stata do-file and return the execution log. Accepts a do-file path, runs it via the configured Stata executable, and can optionally read log content only when return-code errors are detected. Use when you need to run Stata commands, perform regression or statistical analysis, or execute a do-file.get_data_infoGet descriptive statistics and a data preview for a supported data file (.dta, .csv, .tsv, .psv, .xlsx, .xls, .sav, .zsav). Returns overview, variable details, and optional head rows filtered by requested variables. Use when you need to understand a dataset or have no prior knowledge of the data.helpRetrieve documentation and usage information for a Stata command. Use when you need to understand a command's syntax, options, or troubleshoot errors before running it.read_logRead a Stata log file (.log or .smcl) and return its content. Supports full, core, and dict output formats. Use `lines` to return only the first/last N lines.
Ready-to-paste client configs
Paste either block (or both) into your client config, e.g. claude_desktop_config.json or ~/.cursor/mcp.json. We only show a config when the install command is confirmed.
Codebase Memory MCP
{
"mcpServers": {
"deusdata-codebase-memory-mcp": {
"command": "npx",
"args": [
"-y",
"codebase-memory-mcp"
]
}
}
}
Stata MCP
{
"mcpServers": {
"stata-mcp": {
"command": "uvx",
"args": [
"stata-mcp"
]
}
}
}
Frequently asked questions
Codebase Memory MCP is categorized under Knowledge & Memory and uses a local stdio subprocess. Stata MCP belongs to Data Science Tools and uses a local stdio subprocess. Pick Codebase Memory MCP for knowledge & memory work and Stata MCP for data science tools.
Copy the mcpServers block from the config section on this page into your client's config (for example claude_desktop_config.json or ~/.cursor/mcp.json), then fully restart the client.
Codebase Memory MCP is listed as free. Auth: no auth required. Stata MCP is listed as free. Auth: no auth required. If a server needs environment variables such as API keys, define them under the env key in your client's MCP config.
Yes. MCP clients support multiple servers: add deusdata-codebase-memory-mcp and stata-mcp as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, Codebase Memory MCP has a quality signal of 73/100 (Great) with 8 views, 1 installs and 47,004 GitHub stars. Stata MCP has 57/100 (Good) with 7 views, 0 installs and 267 GitHub stars.