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Language Server Agent Protocol (LSAP) SDK - Transforms low-level LSP into high-level cognitive tools for agents

Project description

LSAP: Language Server Agent Protocol

PyPI version License Protocol Version

LSAP (Language Server Agent Protocol) is an open protocol that defines how AI coding agents interact with Language Servers. It transforms low-level LSP capabilities into high-level, Agent-Native cognitive tools, empowering Coding Agents with Repository-Scale Intelligence.

As an Orchestration Layer, LSAP composes atomic LSP operations into semantic interfaces. This aligns with Agent cognitive logic, allowing them to focus on high-level "intent realization" rather than tedious "editor operations."

Core Concept: Atomic Capabilities vs. Cognitive Capabilities

The core difference of LSAP lies in how it defines "capabilities." LSP is designed for editors, providing Atomic operations; whereas LSAP is designed for Agents, providing Cognitive capabilities.

  • LSP (Editor Perspective - Atomic):
    • Editors require very low-level instructions: textDocument/definition (jump), textDocument/hover (hover), textDocument/documentSymbol (outline).
    • The Agent's Dilemma: If an Agent uses LSP directly, it needs to execute a dozen interactions sequentially like a script (open file -> calculate offset -> request definition -> parse URI -> read file -> extract snippet) just to get a useful context.
  • LSAP (Agent Perspective - Cognitive):
    • LSAP encapsulates the complex chain of atomic operations above into a single semantic instruction.
    • Example: A single request to "Find all references" triggers background execution of symbol localization, reference search, and context extraction, returning a consolidated Markdown Report.
sequenceDiagram
    participant Agent as 🤖 Agent
    participant LSAP as 🧠 LSAP Layer
    participant LSP as 🔧 Language Server

    Note left of Agent: Goal: Find all references of "User"

    Agent->>LSAP: 1. Semantic Request (Locate + References)

    rect rgb(245, 245, 245)
        Note right of LSAP: ⚡️ Auto Orchestration
        LSAP->>LSAP: Parse Semantic Anchor (Fuzzy Match)
        LSAP->>LSP: textDocument/hover (Confirm Symbol Info)
        LSAP->>LSP: textDocument/references (Get Reference List)
        LSP-->>LSAP: Return List<Location>

        loop For each reference point
            LSAP->>LSP: textDocument/documentSymbol (Identify Function/Class)
            LSAP->>LSAP: Read Surrounding Code (Context Lines)
        end
    end

    LSAP-->>Agent: 2. Structured Markdown (Callers + Code Context)

Protocol Specification

LSAP is a formally defined protocol with complete JSON Schema specifications for all interaction models. The schema/ directory contains:

  • Request/Response Schemas: Each capability (e.g., definition, outline, rename, etc.) has dedicated request and response schemas.
  • Field Definitions: Precise specifications of input parameters, output fields, and data types.
  • Rendering Templates: Standardized Markdown templates for formatting responses, ensuring consistent agent-facing outputs.

This formal specification ensures:

  • Type Safety: Strong contracts between agents and LSAP implementations.
  • Interoperability: Different LSAP implementations can be swapped without breaking agent workflows.
  • Extensibility: New capabilities can be added following the established schema patterns.

Example schema files: definition.request.json, definition.response.json, reference.request.json, reference.response.json, etc.

Interaction Examples

LSAP's interaction design strictly follows the Markdown-First principle: input expresses intent, and output provides refined knowledge.

1. Find References

Request (using symbol path):

{
  "locate": {
    "file_path": "src/models.py",
    "locate": "User.validate"
  },
  "mode": "references",
  "max_items": 2
}

Alternative: Request (using find pattern):

{
  "locate": {
    "file_path": "src/models.py",
    "find": "def validate<|>("
  },
  "mode": "references",
  "max_items": 2
}

Response:

# References Found

Total references: 12 | Showing: 2

### src/auth/login.py:45

In `LoginHandler.authenticate` (`method`)

```python
44 | def authenticate(credentials):
45 |     if not User.validate(credentials):
46 |         raise AuthError()
```

### src/api/register.py:28

In `register_user` (`function`)

```python
27 | def register_user(new_user_data):
28 |     User.validate(new_user_data)
29 |     db.save(new_user_data)
```

2. File Outline

Request:

{
  "file_path": "src/models.py",
  "mode": "outline"
}

Response:

# Outline for `src/models.py`

## User (`class`)

### User.validate (`method`)

```python
def validate(data: dict) -> bool
```

---

Validate user data before saving.

### User.save (`method`)

```python
async def save(self) -> None
```

## Post (`class`)

### Post.publish (`method`)

```python
async def publish(self) -> PublishResult
```

3. Safe Rename (Two-Step Workflow)

Request (Preview):

{
  "locate": {
    "file_path": "src/models.py",
    "locate": "User.validate"
  },
  "new_name": "validate_data",
  "mode": "rename_preview"
}

Response:

# Rename Preview: `validate` → `validate_data`

ID: `abc123`
Summary: Affects 3 files and 8 occurrences.

## `src/models.py`

Line 15:

```diff
- def validate(data: dict) -> bool:
+ def validate_data(data: dict) -> bool:
```

## `src/auth/login.py`

Line 45:

```diff
- if not User.validate(credentials):
+ if not User.validate_data(credentials):
```

---

> [!TIP]
> To apply this rename, use `rename_execute` with `rename_id="abc123"`.

Request (Execute):

{
  "rename_id": "abc123",
  "exclude_files": ["tests/**"],
  "mode": "rename_execute"
}

Response:

# Rename Applied: `validate` → `validate_data`

Summary: Modified 3 files with 8 occurrences.

- `src/models.py`: 1 occurrence
- `src/auth/login.py`: 4 occurrences
- `src/api/register.py`: 3 occurrences

---

> [!NOTE]
> Rename completed successfully. Excluded files: `tests/**`.
> [!IMPORTANT]
> You must manually rename the symbol in the excluded files to maintain consistency.

I'm Not Convinced...

"LSAP Just Replicates LSP—What's Special?"

While LSP provides atomic operations, LSAP offers composed capabilities that brings more powerful functionalities.

For instance, the Relation API (still in draft, but soon will be released) finds call paths between functions in a single request (handling traversal, cycles, and formatting), a task requiring complex orchestration in raw LSP.

LSAP centralizes these patterns, preventing agents from wasting tokens on orchestration and enabling advanced capabilities like architectural and impact analysis.

"This Adds Complexity"

LSAP centralizes complexity. Instead of every Agent reimplementing LSP orchestration logic, LSAP provides a shared, optimized layer for these common patterns.

Project Structure

  • docs/: Core protocol definitions and Schema documentation.
  • python/: Python SDK reference implementation.
  • typescript/: TypeScript type definitions and utility library.
  • web/: Protocol documentation site.

Alternatives

Claude Code

Claude Code have native LSP supports now - Well they don't.

Serena

serena is a powerful coding agent toolkit providing semantic retrieval and editing capabilities.

Other Projects

Contributing

We welcome contributions! Please see our Contributing Guide for details on development workflows and design principles.

License

MIT

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