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simplify MCP interface for Claude Code

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- Remove unnecessary search parameters: search_mode, recompute_embeddings, file_types, min_score
- Remove leann_clear tool (not needed for Claude Code workflow)
- Streamline search to only use: query, index_name, top_k, complexity
- Keep core tools: leann_index, leann_search, leann_status, leann_list

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>
This commit is contained in:
Andy Lee
2025-08-09 19:01:39 -07:00
parent 42690cb74e
commit 5d21f5bd9d
1 changed files with 2 additions and 112 deletions
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114
packages/leann-core/src/leann/mcp.py
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@@ -111,29 +111,6 @@ This is your first step for any serious codebase work - think of it as giving yo
"maximum": 128,
"description": "Search complexity level. Use 16-32 for fast searches (recommended), 64+ for higher precision when needed.",
},
"search_mode": {
"type": "string",
"enum": ["fast", "balanced", "precise"],
"default": "balanced",
"description": "Search strategy: 'fast' (~2-5s), 'balanced' (~5-10s), 'precise' (~10-20s). Choose based on time vs accuracy needs.",
},
"recompute_embeddings": {
"type": "boolean",
"default": False,
"description": "Recompute embeddings for maximum accuracy. Enable only when precision is more important than speed.",
},
"file_types": {
"type": "array",
"items": {"type": "string"},
"description": "Filter results by file types (e.g., ['py', 'js', 'ts']). Searches all indexed file types if not specified.",
},
"min_score": {
"type": "number",
"minimum": 0.0,
"maximum": 1.0,
"default": 0.0,
"description": "Minimum relevance score threshold (0.0-1.0). Higher values return more relevant but fewer results.",
},
},
"required": ["index_name", "query"],
},
@@ -151,25 +128,6 @@ This is your first step for any serious codebase work - think of it as giving yo
},
},
},
{
"name": "leann_clear",
"description": "🗑️ Safely delete a code index (with confirmation required). Think of it as 'rm -rf' but for your search indexes - be careful!",
"inputSchema": {
"type": "object",
"properties": {
"index_name": {
"type": "string",
"description": "Name of the index to clear/delete.",
},
"confirm": {
"type": "boolean",
"default": False,
"description": "Confirmation flag. Must be set to true to actually perform the deletion.",
},
},
"required": ["index_name"],
},
},
{
"name": "leann_list",
"description": "📋 Show all your indexed codebases - your personal code library! Use this to see what's available for search.",
@@ -263,53 +221,18 @@ This is your first step for any serious codebase work - think of it as giving yo
},
}
# Build command with enhanced parameters
# Build simplified command
cmd = [
"leann",
"search",
args["index_name"],
args["query"],
f"--top-k={args.get('top_k', 5)}",
f"--complexity={args.get('complexity', 32)}",
]
# Handle search mode mapping to set complexity and beam width
search_mode = args.get("search_mode", "balanced")
if search_mode == "fast":
cmd.extend(["--complexity=16", "--beam-width=1"])
elif search_mode == "precise":
cmd.extend(["--complexity=64", "--beam-width=2"])
else: # balanced mode
complexity = args.get("complexity", 32)
cmd.append(f"--complexity={complexity}")
# Handle recompute embeddings
if args.get("recompute_embeddings", False):
cmd.append("--recompute-embeddings")
# Handle file types filtering
file_types = args.get("file_types")
if file_types and isinstance(file_types, list):
# Validate file extensions
valid_extensions = []
for ext in file_types:
if isinstance(ext, str) and ext.strip():
clean_ext = ext.strip()
if not clean_ext.startswith("."):
clean_ext = "." + clean_ext
valid_extensions.append(clean_ext)
if valid_extensions:
cmd.extend(["--filter-extensions", ",".join(valid_extensions)])
result = subprocess.run(cmd, capture_output=True, text=True)
# Handle min_score filtering in post-processing if needed
min_score = args.get("min_score", 0.0)
if min_score > 0.0 and result.returncode == 0:
# Note: This is a basic implementation. For full support,
# the CLI would need to return structured data for filtering
pass
elif tool_name == "leann_status":
if args.get("index_name"):
# Check specific index status - for now, we'll use leann list and filter
@@ -319,39 +242,6 @@ This is your first step for any serious codebase work - think of it as giving yo
# Show all indexes status
result = subprocess.run(["leann", "list"], capture_output=True, text=True)
elif tool_name == "leann_clear":
index_name = args["index_name"]
confirm = args.get("confirm", False)
if not confirm:
return {
"jsonrpc": "2.0",
"id": request.get("id"),
"result": {
"content": [
{
"type": "text",
"text": f"Warning: This will permanently delete index '{index_name}'. To proceed, call this tool again with confirm=true.",
}
]
},
}
# For clearing, we need to implement this in the CLI
# For now, we'll return a message explaining the limitation
return {
"jsonrpc": "2.0",
"id": request.get("id"),
"result": {
"content": [
{
"type": "text",
"text": f"Clear functionality for index '{index_name}' is not yet implemented in CLI. You can manually delete the index files in .leann/indexes/{index_name}/",
}
]
},
}
elif tool_name == "leann_list":
result = subprocess.run(["leann", "list"], capture_output=True, text=True)