@@ -483,7 +483,7 @@
Protocol (MCP) server that indexes a codebase into a persistent knowledge graph of functions,
classes, call chains, HTTP routes, and cross-service links. Instead of reading files one at a time,
an AI coding agent queries the graph — answering structural questions with roughly 120x fewer
- tokens. It parses 158 languages and ships as a native executable with authenticated release-owned assets;
+ tokens. It parses 161 languages and ships as a native executable with authenticated release-owned assets;
the native install needs no language runtime.
- The two-layer pipeline runs a fast syntactic tree-sitter pass for every one of the 158 languages,
+ The two-layer pipeline runs a fast syntactic tree-sitter pass for every one of the 161 languages,
then a type-aware Hybrid LSP pass on top for the families above. Languages without a Hybrid LSP pass
yet fall back to textual resolution, so you always get an answer.
-
158 languages
+
161 languages
Python, Go, JS, TS, TSX, Rust, Java, C++, C#, C, PHP, Ruby, Kotlin, Scala, Zig, Elixir, Haskell, OCaml, Swift, Dart, Lean 4, and many more via vendored tree-sitter grammars compiled into the binary.
diff --git a/docs/llms.txt b/docs/llms.txt
index ce927ad91..4a18a3ac4 100644
--- a/docs/llms.txt
+++ b/docs/llms.txt
@@ -1,6 +1,6 @@
# codebase-memory-mcp
-> An open-source Model Context Protocol (MCP) server that indexes a codebase into a persistent knowledge graph of functions, classes, call chains, HTTP routes, and cross-service links. AI coding agents query the graph instead of reading files one by one, answering structural questions with roughly 120x fewer tokens (~3,400 vs ~412,000 across five structural queries). Parses 158 languages via vendored tree-sitter grammars, with Hybrid LSP semantic type resolution for Python, TypeScript/JavaScript, PHP, C#, Go, C/C++, Java, Kotlin, and Rust. It also generates semantic graph edges (SEMANTICALLY_RELATED for vocabulary-mismatch matches, SIMILAR_TO for near-clone detection) and supports semantic vector search via bundled nomic-embed-code embeddings compiled into the native executable — no API key, no Ollama, no Docker. Ships a native executable with an authenticated integration asset; the UI variant adds one content-addressed frontend pack. All processing is local — the embeddings run on-device; there is no embedded LLM and no API key.
+> An open-source Model Context Protocol (MCP) server that indexes a codebase into a persistent knowledge graph of functions, classes, call chains, HTTP routes, and cross-service links. AI coding agents query the graph instead of reading files one by one, answering structural questions with roughly 120x fewer tokens (~3,400 vs ~412,000 across five structural queries). Parses 161 languages via vendored tree-sitter grammars, with Hybrid LSP semantic type resolution for Python, TypeScript/JavaScript, PHP, C#, Go, C/C++, Java, Kotlin, and Rust. It also generates semantic graph edges (SEMANTICALLY_RELATED for vocabulary-mismatch matches, SIMILAR_TO for near-clone detection) and supports semantic vector search via bundled nomic-embed-code embeddings compiled into the native executable — no API key, no Ollama, no Docker. Ships a native executable with an authenticated integration asset; the UI variant adds one content-addressed frontend pack. All processing is local — the embeddings run on-device; there is no embedded LLM and no API key.
## Key facts
diff --git a/pkg/chocolatey/codebase-memory-mcp.nuspec b/pkg/chocolatey/codebase-memory-mcp.nuspec
index 0c8f3f177..d0509ecf1 100644
--- a/pkg/chocolatey/codebase-memory-mcp.nuspec
+++ b/pkg/chocolatey/codebase-memory-mcp.nuspec
@@ -18,7 +18,7 @@ release-owned runtime assets. Chocolatey retains the complete extracted runtime
set and exposes its executable through a PATH shim.
Full indexes an average repository in milliseconds, the Linux kernel (28M LOC) in
-3 minutes. Answers structural queries in under 1ms. Supports 159 languages via
+3 minutes. Answers structural queries in under 1ms. Supports 161 languages via
vendored tree-sitter grammars. No hosted service or API key. Plug and play across
11 coding agents including Claude Code, Codex CLI, Gemini CLI, and Zed.
diff --git a/pkg/npm/README.md b/pkg/npm/README.md
index 2fed116ab..d46191594 100644
--- a/pkg/npm/README.md
+++ b/pkg/npm/README.md
@@ -7,7 +7,7 @@
**The fastest and most efficient code intelligence engine for AI coding agents.** Full-indexes an average repository in milliseconds, the Linux kernel (28M LOC, 75K files) in 3 minutes. Answers structural queries in under 1ms. This npm wrapper downloads, verifies, and caches the selected native runtime set: the executable, its authenticated integration asset, and—when requested—the content-addressed UI pack.
-High-quality parsing through [tree-sitter](https://tree-sitter.github.io/tree-sitter/) AST analysis across 158 languages — producing a persistent knowledge graph of functions, classes, call chains, HTTP routes, and cross-service links. 15 MCP tools. No hosted service or API key; this package requires Node.js to manage and launch the cached native runtime set. Plug and play across 44 automatic/conditional client surfaces.
+High-quality parsing through [tree-sitter](https://tree-sitter.github.io/tree-sitter/) AST analysis across 161 languages — producing a persistent knowledge graph of functions, classes, call chains, HTTP routes, and cross-service links. 15 MCP tools. No hosted service or API key; this package requires Node.js to manage and launch the cached native runtime set. Plug and play across 44 automatic/conditional client surfaces.
## Installation
@@ -29,7 +29,7 @@ Restart your agent. Say **"Index this project"** — done.
- **Extreme indexing speed** — Linux kernel (28M LOC, 75K files) in 3 minutes. RAM-first pipeline with LZ4 compression and in-memory SQLite.
- **Plug and play** — verified native runtime sets for macOS (arm64/amd64), Linux (arm64/amd64), and Windows (arm64/amd64). No Docker or API keys; Node.js owns package download, cache repair, and launch.
-- **158 languages** — vendored tree-sitter grammars compiled into the binary. Nothing to install, nothing that breaks.
+- **161 languages** — vendored tree-sitter grammars compiled into the binary. Nothing to install, nothing that breaks.
- **120x fewer tokens** — 5 structural queries: ~3,400 tokens vs ~412,000 via file-by-file search.
- **44 supported automatic/conditional client surfaces** — `install` configures the appropriate MCP, durable-context, and documented hook surfaces without widening client permissions.
- **Detected automatically (38)** — Claude Code, Codex CLI, Gemini CLI, Zed, OpenCode, Antigravity, Aider, KiloCode, VS Code, Cursor, Windsurf, Augment / Auggie, OpenClaw, Kiro, Junie, Hermes, OpenHands, Cline, Warp, Qwen Code, GitHub Copilot CLI, Factory Droid, Crush, Goose, Mistral Vibe, Grok Build, Qoder CLI, Kimi Code CLI, GitLab Duo CLI, Rovo Dev CLI, Amp, Devin CLI / Local, Tabnine, Amazon Q Developer IDE, CodeBuddy Code CLI, IBM Bob Shell, Pochi, and Pi.
diff --git a/scripts/package-release.sh b/scripts/package-release.sh
index 0aa00d4d2..1ee35c539 100755
--- a/scripts/package-release.sh
+++ b/scripts/package-release.sh
@@ -293,7 +293,7 @@ build_mcpb_bundle() {
"name": "codebase-memory-mcp",
"display_name": "Codebase Memory",
"version": "$mcpb_version",
- "description": "Codebase knowledge graph for AI agents — 159 languages, sub-ms queries, 99% fewer tokens.",
+ "description": "Codebase knowledge graph for AI agents — 161 languages, sub-ms queries, 99% fewer tokens.",
"author": { "name": "DeusData", "url": "https://github.com/DeusData" },
"repository": { "type": "git", "url": "https://github.com/DeusData/codebase-memory-mcp" },
"homepage": "https://deusdata.github.io/codebase-memory-mcp/",
diff --git a/server.json b/server.json
index dc49e586e..93bcccc3b 100644
--- a/server.json
+++ b/server.json
@@ -2,7 +2,7 @@
"$schema": "https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json",
"name": "io.github.DeusData/codebase-memory-mcp",
"title": "Codebase Memory",
- "description": "Codebase knowledge graph for AI agents \u2014 159 languages, sub-ms queries, 99% fewer tokens.",
+ "description": "Codebase knowledge graph for AI agents \u2014 161 languages, sub-ms queries, 99% fewer tokens.",
"repository": {
"url": "https://github.com/DeusData/codebase-memory-mcp",
"source": "github"
diff --git a/tests/test_language_count_contract.sh b/tests/test_language_count_contract.sh
index 7093e41d4..1b664c0d1 100644
--- a/tests/test_language_count_contract.sh
+++ b/tests/test_language_count_contract.sh
@@ -73,7 +73,7 @@ EXEMPT=(
)
failures=0
-claims=0
+distinct=0
for path in "${SURFACES[@]}"; do
if [[ ! -f "$path" ]]; then
@@ -90,7 +90,7 @@ for path in "${SURFACES[@]}"; do
continue
fi
while IFS= read -r n; do
- claims=$((claims + 1))
+ distinct=$((distinct + 1))
if [[ "$n" != "$expected" ]]; then
echo "FAIL: $path claims $n languages, $expected grammars are vendored" >&2
failures=$((failures + 1))
@@ -120,4 +120,4 @@ if ((failures > 0)); then
exit 1
fi
-echo "Language-count contract passed ($claims claims across ${#SURFACES[@]} surfaces, registry = $expected)"
+echo "Language-count contract passed (${#SURFACES[@]} surfaces, $distinct distinct value(s) checked, $expected grammars vendored)"