CDB-MCP
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@CDB-MCPAnalyze the crash dump at C:\dumps\crash.dmp"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
CDB-MCP: CDB Debugger MCP Server
Exposes Microsoft CDB (Console Debugger) capabilities through the Model Context Protocol (MCP), enabling LLMs to perform live debugging, dump analysis, remote debugging, and more.
Design Philosophy
The server is a transport layer between the LLM and cdb.exe, not an abstraction layer for CDB commands.
The LLM already has knowledge of CDB/WinDbg commands. The server only does three things:
Manage cdb.exe subprocesses (start/stop/list sessions)
Forward commands and output (LLM sends CDB command string -> forwarded to cdb.exe -> raw text output returned)
Provide Ctrl+Break interrupt (cannot be done via stdin text; requires an OS signal)
It does not wrap specific CDB commands, does not parse output into JSON, and does not restrict command syntax.
Related MCP server: dump-analyzer-mcp-server
Tools
Tool | Description |
| Start cdb.exe (launch / attach / dump / remote) |
| Close or detach a session |
| List active sessions |
| Send a CDB command string; returns status ( |
| Poll the output buffer of the current pending command (sends no command) |
| Wait for the current pending command to complete |
| Send Ctrl+Break to interrupt the running target |
Prerequisites
Windows Debugging Tools -- provides
cdb.exeInstall via Windows SDK: select "Debugging Tools for Windows"
Or install WinDbg Preview from Microsoft Store
Common path:
C:\Program Files (x86)\Windows Kits\10\Debuggers\x64\cdb.exe
Python 3.11+ and uv
Install uv from https://docs.astral.sh/uv/
Installation
git clone https://github.com/cc682/cdb-mcp.git cdb-mcp
cd cdb-mcp
# Create virtual environment and install dependencies
uv venv --python 3.12 .venv
uv syncMCP Client Configuration
VS Code Copilot
Create .vscode/mcp.json in the project root:
{
"servers": {
"cdb-mcp": {
"type": "stdio",
"command": "uv",
"args": [
"run",
"--directory",
"C:\\path\\to\\cdb-mcp",
"python",
"-m",
"cdb_mcp"
],
"env": {
"CDB_MCP_CDB_PATH": "C:\\Program Files (x86)\\Windows Kits\\10\\Debuggers\\x64\\cdb.exe",
"CDB_MCP_SYMBOLS_PATH": "srv*C:\\symbols*https://msdl.microsoft.com/download/symbols"
}
}
}
}Claude Desktop
Edit %APPDATA%\Claude\claude_desktop_config.json:
{
"mcpServers": {
"cdb-mcp": {
"command": "uv",
"args": [
"run",
"--directory",
"C:\\path\\to\\cdb-mcp",
"python",
"-m",
"cdb_mcp"
],
"env": {
"CDB_MCP_CDB_PATH": "C:\\Program Files (x86)\\Windows Kits\\10\\Debuggers\\x64\\cdb.exe",
"CDB_MCP_SYMBOLS_PATH": "srv*C:\\symbols*https://msdl.microsoft.com/download/symbols"
}
}
}
}Replace
C:\\path\\to\\cdb-mcpwith the actual project path.
Environment Variables
Variable | Description | Default |
| Full path to cdb.exe | Auto-discovered |
| Symbol path (semicolon-separated) | Microsoft symbol server |
| Source code path | Empty |
| Max concurrent sessions |
|
| Default command timeout (seconds) |
|
| Output buffer line count |
|
Symbol path format: srv*local_cache_dir*symbol_server;extra_path1;extra_path2
When debugging your own program, add the directory containing your PDB:
srv*C:\symbols*https://msdl.microsoft.com/download/symbols;C:\MyProject\binVerification
After configuration, reload the VS Code window (Ctrl+Shift+P -> Developer: Reload Window).
Type /tools in chat to see the 7 cdb-mcp tools.
If tools are disabled, set their status to Allow in the /tools panel.
Usage Examples
Dump Analysis
1. create_session(type="dump", target="C:\dumps\crash.dmp")
-> returns session_id
2. execute(command="!analyze -v", timeout=600)
-> {"status": "completed", "output": "analysis results..."}
3. execute(command="k")
-> {"status": "completed", "output": "call stack..."}
4. execute(command="lm")
-> returns module list
5. close_session()Live Debugging (Breakpoints)
1. create_session(type="live_launch", target="C:\app\myapp.exe")
2. execute(command="bp myapp!main") -> set breakpoint
3. execute(command="g") -> {"status": "completed"} breakpoint hit
4. execute(command="k") -> view call stack
5. execute(command="dv") -> view local variables
6. execute(command="p") -> single step
7. close_session()Long-Running Commands (Pending Polling)
1. execute(command="g", timeout=2)
-> {"status": "pending", "output": "program starting..."}
2. get_output() -> poll, no command sent
-> {"status": "pending", "output": "tick 1\ntick 2\n...", "command": "g"}
3. get_output() -> keep polling
-> {"status": "pending", "output": "tick 1-10\n...", "command": "g"}
4. interrupt() -> interrupt the running target
-> {"status": "interrupted"}
5. wait_for_prompt(timeout=10) -> wait for prompt
-> {"status": "completed", "output": "post-interrupt output..."}
6. execute(command="k") -> session recovered
-> {"status": "completed", "output": "call stack..."}Tech Stack
Language: Python 3.11+
MCP SDK:
mcp2.0 (official Python SDK)Debug backend:
cdb.exe(Windows Debugging Tools)Package manager:
uv/pipTesting:
pytest
License
MIT
Available Tools
7 toolsclose_sessionA
Close a debug session, terminating the cdb.exe subprocess.
With detach=true the debugger detaches (target process keeps running). With detach=false the session is closed directly.
| Name | Required | Description | Default |
|---|---|---|---|
| detach | No | ||
| session_id | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It transparently warns that the tool terminates the cdb.exe subprocess and explains the impact on the target process for both detach settings. This is strong, though it omits edge cases like invalid session_id or error behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two short sentences with the core action front-loaded. It includes only essential details about detach behavior, with no wasted words or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is fairly simple with two optional parameters, and an output schema exists (so return values needn't be explained). However, the description omits the role of session_id (e.g., what happens if null) and provides no usage guidance. It is adequate but has clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It explains the detach parameter clearly, but the session_id parameter is never described. The name is somewhat self-explanatory, but the description adds no meaning for session_id, leaving a partial gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Close a debug session, terminating the cdb.exe subprocess.' This uses a specific verb and resource, and it is clearly distinct from sibling tools like create_session, list_sessions, and execute.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains the two behavioral modes (detach true vs false) but does not explicitly state when to use this tool versus alternatives, nor does it exclude any cases. The detach explanation implies usage, but no explicit guidance or alternative references are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
create_sessionA
Create a CDB debug session by launching a cdb.exe subprocess.
Four session types:
live_launch: launch a new process under the debugger (target=exe path, args=launch args)
live_attach: attach to a running process (target=PID)
dump: load a dump file (target=dump file path)
remote: connect to a remote debug server (target=connection string)
After creation, use the execute tool to send CDB commands.
| Name | Required | Description | Default |
|---|---|---|---|
| args | No | ||
| type | Yes | ||
| target | Yes | ||
| image_path | No | ||
| source_path | No | ||
| symbols_path | No | ||
| engine_options | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that the tool launches a subprocess and describes the target semantics for each session type. It does not mention resource cleanup or failure behavior, but the launch mechanism and the distinction between live_attach (PID) and live_launch (exe path) add meaningful behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, front-loaded with the core purpose, and uses a clear bulleted list for the four session types. Every sentence adds value, and it avoids redundant restatement of the schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description provides a solid overview of core session creation but omits details about optional parameters and session lifecycle. It does mention the next step (use execute), which helps integrate with siblings. Given the tool has 7 parameters and no annotations, the description is not fully complete for advanced usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It explains the semantics of 'type' and 'target' for all four session types, and 'args' for live_launch. However, it does not explain image_path, source_path, symbols_path, or engine_options, leaving significant gaps for 5 of the 7 parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool creates a CDB debug session by launching a cdb.exe subprocess. It details four distinct session types (live_launch, live_attach, dump, remote) with corresponding target definitions, which distinguishes it from siblings like execute or get_output.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly lists the four session types and when each is appropriate (e.g., attach to a running process with a PID, load a dump with a file path). It also notes to use the execute tool after creation for sending commands, providing clear workflow guidance. However, it does not explicitly contrast with alternatives like list_sessions or close_session, though the context makes this implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
executeA
Send a CDB command to the current debug session. Returns status and output.
This is the core tool for interacting with CDB. The LLM constructs valid CDB command strings; the server forwards them to cdb.exe.
Returns JSON: {"status": "completed", "output": "..."} -- command finished {"status": "pending", "output": "..."} -- command timed out but still running {"status": "error", "output": "", "error": "..."} -- error occurred
When status is "pending":
The command is still running in CDB (not interrupted)
Use get_output() to poll for more output
Use interrupt() to interrupt the command
Use wait_for_prompt() to wait for completion
Common commands:
g : continue execution (often returns pending; use interrupt to stop)
t / p / gu : step into / step over / step out
bp / bc / bl : set / remove / list breakpoints
r : display registers
k : display call stack
~ : list threads
lm : list modules
dv : display local variables
?? expr : evaluate expression
u addr : disassemble
d addr L n : read memory
!analyze -v : automatic crash analysis (slow; use large timeout)
Note: q/qq/qd commands are blocked (use close_session instead).
| Name | Required | Description | Default |
|---|---|---|---|
| command | Yes | ||
| timeout | No | ||
| session_id | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It thoroughly explains return statuses (completed, pending, error), what 'pending' means, and how to handle it. It also alerts the user to dangerous or slow commands (e.g., !analyze -v), blocked commands, and the fact that commands are forwarded to cdb.exe. This goes well beyond a basic description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Although the description is long, it is efficiently structured with clear sections for return values, pending behavior, and common commands. Every sentence adds practical value—examples, cautionary notes, or status handling—so the length is justified and the content is front-loaded with the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a CDB command execution tool, the description is remarkably complete. It covers return formats, asynchronous behavior, common command usage, safety exclusions, and provides pointers to sibling tools for each scenario. The output schema is embedded in the description, and the parameter guidance is sufficient for an agent to operate correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, so the description must compensate. It explains that 'command' is a CDB string and hints at the timeout parameter (e.g., 'use large timeout' for !analyze -v), but it does not explicitly document the 'timeout' or 'session_id' parameters or their expected formats. This partial compensation earns a mid-range score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a clear, specific verb and resource: 'Send a CDB command to the current debug session.' It further identifies this as 'the core tool for interacting with CDB,' explicitly distinguishing it from sibling tools like get_output, interrupt, and close_session, which handle related but distinct operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool versus alternatives: it notes that pending commands should be followed by get_output, interrupt, or wait_for_prompt, and that q/qq/qd are blocked, directing the agent to 'use close_session instead.' This makes when-to-use and when-not-to-use behavior clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_outputA
Get the output status and content of the current command.
Used to poll a command's progress after execute() returns pending. Does not send any command to CDB; only reads the existing output buffer.
Returns JSON: {"status": "pending", "output": "...", "command": "g"} -- command still running; output is what has been produced so far {"status": "idle", "output": "", "command": null} -- no command is executing
Typical usage:
execute("g") -> returns pending
get_output() -> check for new output (e.g. breakpoint hit info)
If output shows breakpoint reached, call interrupt() to stop
If still running, keep polling with get_output()
| Name | Required | Description | Default |
|---|---|---|---|
| session_id | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description fully discloses behavioral traits: it only reads the existing output buffer, never sends commands to CDB, and gives exact JSON return formats for pending and idle states. This goes beyond basic expectations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections, code blocks, and a numbered usage flow. Every sentence contributes value, and the length is justified by the detailed examples and behavioral disclosures.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description provides rich context for how to use the tool, its behavior, and expected outputs. However, it omits any explanation of the session_id parameter or how the 'current command' is determined in a multi-session context, leaving a minor completeness gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has one optional parameter, session_id, but the description never mentions it, leaving its purpose and necessity ambiguous. Since schema description coverage is 0%, the description should compensate but does not, which is a clear gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly identifies the tool as fetching output status and content for the current command, using a specific verb and resource. It distinguishes itself from siblings by describing its role as a polling mechanism after execute() returns pending.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use the tool ('after execute() returns pending') and provides a typical usage flow with numbered steps. It also clarifies it does not send commands to CDB, which helps avoid misuse.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
interruptA
Interrupt the running debug target (send Ctrl+Break).
Used after execute('g') returns pending, to stop the target. CDB will stop the target and display a new prompt. After interrupt, use get_output() to see the post-interrupt output.
| Name | Required | Description | Default |
|---|---|---|---|
| session_id | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It explains the effect ('CDB will stop the target and display a new prompt') and the post-interrupt step. It lacks detail on error cases or behavior when the target is not running, but covers the core action well.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, front-loaded with the primary purpose, and each sentence adds value: purpose, usage trigger, and follow-up. No redundant or extraneous content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with one optional parameter and an output schema. The description covers the main workflow (when to interrupt, what happens, what to do next). It could mention error cases (e.g., interrupting when nothing is running), but overall it is sufficiently complete for an informed agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has only one optional parameter (session_id) with 0% schema description coverage. The description does not mention this parameter at all, leaving the agent to infer its meaning from sibling tools or the schema defaults. This is a clear gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Interrupt the running debug target (send Ctrl+Break).' This uses a specific verb and resource, and it distinguishes the tool from siblings like execute and get_output by focusing on stopping the target.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit contextual guidance: 'Used after execute('g') returns pending, to stop the target.' It also advises the follow-up action to get_output(). However, it does not explicitly mention when not to use the tool or name alternative tools for similar scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_sessionsA
List all active debug sessions and their states.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses that only active sessions are returned, which is a useful behavioral trait. However, it does not explicitly state that the operation is read-only or free of side effects, though 'list' implies this.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, direct sentence with no filler. It is appropriately front-loaded and minimal.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple, no-argument list tool with an existing output schema, the description sufficiently explains what the tool does and what it returns. No additional context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the baseline is 4. The description adds no parameter-specific information, which is acceptable given the empty schema and 100% schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('List') and resource ('debug sessions') with a scope qualifier ('active') and includes the state information. It clearly distinguishes itself from sibling tools like create_session and close_session.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for checking active sessions, but does not explicitly state when to use it versus alternatives like execute or get_output. No exclusions are mentioned, though the context of sibling tools makes the purpose clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
wait_for_promptA
Wait for the current pending command to complete (CDB prompt to appear).
Used after execute() returns pending, to continue waiting for command completion. If no command is pending, returns idle status.
Returns JSON: {"status": "completed", "output": "..."} -- command finished {"status": "pending", "output": "..."} -- still running, timed out again {"status": "idle", "output": ""} -- no command is executing
| Name | Required | Description | Default |
|---|---|---|---|
| timeout | No | ||
| session_id | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavior itself. It does this well by describing the wait semantics, the idle state when no command is pending, and the three possible return statuses with sample JSON. However, it does not explain side effects (e.g., whether output is consumed) or timeout details beyond 'timed out again,' leaving some ambiguity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded with the primary purpose. The return JSON example is useful and not overly verbose. Minor redundancy exists (e.g., 'returns idle status' repeated), but overall it is efficient and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the return format and basic usage pattern, which is helpful given the output schema exists. However, it omits key context about session_id and timeout semantics, which are essential for correct invocation. For a tool with two optional parameters and a rich return structure, the description should address these to be complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must explain parameters. It mentions timeout indirectly via "timed out again" but never explains that the timeout parameter controls waiting duration. It does not mention session_id at all, which is critical for multi-session scenarios. The parameter names are somewhat self-explanatory, but the description adds little to their semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: "Wait for the current pending command to complete" with a specific verb (wait) and resource (pending command). It also distinguishes from siblings by referencing the execute() flow and the CDB prompt, making it clear this is a polling/waiting operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says "Used after execute() returns pending, to continue waiting for command completion," providing clear when-to-use guidance. It does not explicitly mention alternatives or exclusions, but the context is strong enough to guide the agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
7 tool updates
v0.1.0- First observed
close_session - First observed
create_session - First observed
execute - First observed
get_output - First observed
interrupt - First observed
list_sessions - First observed
wait_for_prompt
TDQS
Each tool has a clearly distinct purpose: session lifecycle (create/close/list), command execution, output polling, waiting, and interrupting. Even the similar get_output and wait_for_prompt are differentiated by their descriptions (reading buffer vs. waiting for prompt), leaving no real ambiguity.
Names mostly follow a verb_noun pattern (create_session, close_session, list_sessions, get_output), with a few bare verbs (execute, interrupt) that still clearly indicate actions. The style is consistent and readable, with only minor deviation from the noun suffix.
Seven tools is well-scoped for a debugger integration. Each tool covers a necessary aspect of session and command management without redundancy, and the count is appropriate for the complexity of CDB interaction.
The tool set covers the full debug session lifecycle: create, close, list, execute arbitrary commands, and handle asynchronous output (poll, wait, interrupt). There are no obvious dead ends—any CDB command can be run, and pending operations can be managed. The only theoretical gap (dedicated breakpoint tools) is handled by the generic execute tool.
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