@zesun33/mcp-openroad
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., "@@zesun33/mcp-openroadRun end-to-end P&R on counter_netlist.v (top: counter) with a 1ns clock and report timing."
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.
@zesun33/mcp-openroad
Model Context Protocol (MCP) server for open-source digital ASIC physical design (place-and-route) and static timing analysis via OpenROAD.
mcp-openroad equips AI coding agents and IDEs (Cursor, Windsurf, GitHub Copilot / OpenAI Codex, Claude Code, Google Antigravity, OpenCode, Cline) with structured tools to execute physical design (P&R) flows over standard cell netlists. It automates floorplanning, analytical cell placement, clock tree synthesis (CTS), global/detailed routing, and static timing analysis (STA), transforming verbose multi-thousand-line terminal logs into clean, low-token JSON metrics ($< 150$ tokens).
⚡ Quick Tour: See It in Action
Why AI Agents Need mcp-openroad
Without | With |
Dumps 10,000+ lines of raw C++ log output into LLM context | Clean structured JSON with < 150 tokens of exact metrics |
Timing slack (WNS/TNS) buried deep in STA reports | Direct |
Manual setup of tech LEFs, cell LEFs, and timing libraries | Zero-config bundled platform (Nangate45 + Sky130 support) |
Host installation requires complex C++ dependencies and conda | Isolated rootless Podman ( |
Unplaced cells and DRC shorts require visual inspection | Pinpointed DRC counts, HPWL, and displacement metrics |
Real Agent Scenarios in 60 Seconds
1. Probing the Environment (Zero-Config Verification)
// Tool Call: openroad_toolchain_info
{
"runtime": "podman",
"image": "localhost/zesun33/asic",
"openroadVersion": "2.0-12381-g01bba3695",
"staVersion": "OpenSTA 2.6.0",
"platforms": ["nangate45", "sky130"]
}2. Automated Floorplanning & I/O Pin Placement (200ms)
// Tool Call: openroad_floorplan {"netlist_file": "counter_netlist.v", "top_module": "counter", "die_width": 50, "die_height": 50}
{
"success": true,
"dieArea": { "llx": 0, "lly": 0, "urx": 50, "ury": 50, "width": 50, "height": 50 },
"coreArea": { "llx": 5.13, "lly": 5.6, "urx": 44.84, "ury": 44.8, "width": 39.71, "height": 39.2 },
"pinsPlaced": 6,
"defFile": "counter_fp.def"
}3. End-to-End P&R and Static Timing Closure (400ms)
// Tool Call: openroad_pnr {"netlist_file": "counter_netlist.v", "top_module": "counter", "clock_period_ns": 1.0}
{
"success": true,
"topModule": "counter",
"platform": "nangate45",
"cellCount": 13,
"utilization": 1.93,
"hpwl": 106.6,
"timing": {
"timingMet": true,
"wns": 0.0,
"tns": 0.0,
"clockPeriod": 1.0
},
"defFile": "counter_routed.def",
"warnings": [],
"errors": []
}Related MCP server: EDA Tools MCP Server
Tools Exposed
Tool | Parameters | Engine | Description |
|
| OpenROAD Full Flow | Automated end-to-end physical design (floorplanning, placement, routing, and STA) returning area, utilization, wirelength, and timing slack metrics. |
|
|
| Initializes ASIC floorplan boundaries, core/die sizing, and I/O pin placement, generating a floorplan DEF file. |
|
|
| Performs standard cell global analytical placement (RePLace) and legalized detailed placement (DPL). |
|
|
| Performs global routing (FastRoute) and detailed routing, reporting wirelength and DRC violation metrics. |
|
| OpenSTA | Performs static timing analysis on placed or routed DEF files, reporting Worst Negative Slack (WNS), Total Negative Slack (TNS), and critical paths. |
|
| Probe | Returns container/host runtime and version information for OpenROAD, OpenSTA, and supported platform PDKs. |
Client Configuration
To register mcp-openroad with your AI IDE or agent, add it to your configuration file (e.g., .cursor/mcp.json, claude_desktop_config.json, or Windsurf settings):
{
"mcpServers": {
"openroad": {
"command": "node",
"args": ["/path/to/mcp-openroad/dist/index.js"],
"env": {
"MCP_OPENROAD_RUNTIME": "podman",
"MCP_OPENROAD_IMAGE": "localhost/zesun33/asic"
}
}
}
}Universal Compatibility
Works out-of-the-box across all modern AI coding environments:
Cursor: Configure in
.cursor/mcp.json.Windsurf: Configure in
~/.codeium/windsurf/mcp_config.json.GitHub Copilot / OpenAI Codex: Configure via Copilot MCP settings or Codex tool proxy.
Claude Code: Configure via
claude mcp add openroad node /path/to/dist/index.js.Google Antigravity: Load as workspace MCP server in
antigravity.json.OpenCode & Cline: Direct stdio JSON-RPC connection.
Verification & Testing
Strict 6-gate verification suite matching the portfolio engineering standard:
# Full verification (all 6 gates)
./scripts/verify.sh
# Target specific gates
./scripts/verify.sh --gate 1 # Spec lock & package integrity
./scripts/verify.sh --gate 2 # Static build (TypeScript)
./scripts/verify.sh --gate 3 # Unit tests (parsers & schema contract)
./scripts/verify.sh --gate 4 # Live Podman container integration tests
./scripts/verify.sh --gate 5 # Stdio JSON-RPC contract check
./scripts/verify.sh --gate 6 # Documentation validationLicense
Apache-2.0 © 2026 Md Zesun Ahmed Mia
Available Tools
6 toolsopenroad_floorplanA
Initializes ASIC floorplan boundaries, core/die sizing, and I/O pin placement using OpenROAD, generating a floorplan DEF file.
| Name | Required | Description | Default |
|---|---|---|---|
| cwd | No | Optional working directory. | |
| die_width | No | Die width in microns (default: 60). | |
| die_height | No | Die height in microns (default: 60). | |
| output_def | No | Output floorplan DEF file path. | |
| timeout_ms | No | Timeout in milliseconds. | |
| top_module | Yes | Name of the top-level module. | |
| core_margin | No | Margin between die and core in microns (default: 5). | |
| netlist_file | Yes | Gate-level Verilog netlist file path. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry behavioral disclosure. It does communicate the main side effect—generating a floorplan DEF file via OpenROAD—but does not disclose overwrite behavior for an existing output_def, execution characteristics, or failure modes. This is adequate but has clear transparency gaps.
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?
One focused sentence with no filler; the primary action and output artifact are front-loaded. Every phrase carries information.
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 is sufficient for a simple floorplan initialization step, but with no output schema or annotations it leaves out useful operational context: whether existing DEF files are overwritten, what the tool returns on success, and how this step sequences into the sibling P&R tools.
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 100%, so the baseline is 3. The description adds only conceptual grouping ('core/die sizing', 'I/O pin placement') that maps loosely to die_width, die_height, and core_margin, but no new parameter-level meaning.
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 ('Initializes') and a concrete resource: ASIC floorplan boundaries, core/die sizing, and I/O pin placement. It also names the deliverable, a floorplan DEF file, which separates it from the place/route/STA sibling tools even without naming them explicitly.
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 never states when to run this tool versus openroad_place, openroad_route, or openroad_pnr. It implies the floorplan step from the 'floorplan' terminology and DEF output, but leaves workflow ordering and alternative selection to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
openroad_placeB
Performs standard cell global analytical placement (RePLace) and legalized detailed placement (DPL) on a floorplan DEF file.
| Name | Required | Description | Default |
|---|---|---|---|
| cwd | No | Optional working directory. | |
| density | No | Target placement density (default: 0.4). | |
| output_def | No | Output placed DEF file path. | |
| timeout_ms | No | Timeout in milliseconds. | |
| top_module | Yes | Name of the top-level module. | |
| floorplan_def | Yes | Floorplan DEF file path. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the full burden of disclosing side effects, safety, and preconditions. It only restates the placement operation and says nothing about whether the input DEF is modified, whether an output file is written, or what failure conditions exist. This is a significant transparency gap for a transformation tool.
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?
A single front-loaded sentence that states the verb, scope, and target file type in one pass. There is no repetition of schema fields and no filler, making it highly concise and efficient.
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?
With six parameters, no annotations, and no output schema, the description should explain prerequisites, side effects, and expected results. It only covers the transformation itself, leaving the agent to guess about flow order and what the tool returns or writes.
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 100%, so the baseline is 3. The description adds general context about the placement operation but does not elaborate on parameters like density or output_def beyond their schema descriptions.
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 specific verb ('Performs'), names the resource ('standard cell ... placement'), and distinguishes the step by naming both global analytical placement (RePLace) and legalized detailed placement (DPL). This clearly differentiates it from sibling floorplan, route, and STA tools.
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 placement step is implied by the operation and the sibling tool names, but the description never explicitly states when to use this tool versus openroad_floorplan, openroad_route, or openroad_pnr, nor does it mention prerequisites. An agent can infer usage context only from the tool name and flow terminology.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
openroad_pnrA
Performs end-to-end automated digital ASIC physical design (floorplanning, placement, routing, and static timing analysis) on a gate-level netlist using OpenROAD, returning area, utilization, wirelength, and timing slack metrics.
| Name | Required | Description | Default |
|---|---|---|---|
| cwd | No | Optional working directory where source files reside. | |
| sdc_file | No | Optional SDC timing constraints file path. | |
| output_def | No | Optional output routed DEF file path. | |
| timeout_ms | No | Timeout in milliseconds (default: 45000). | |
| top_module | Yes | Name of the top-level module to place and route. | |
| netlist_file | Yes | Gate-level Verilog netlist file path. | |
| clock_period_ns | No | Target clock period in ns if no SDC provided (default: 1.0). | |
| core_utilization | No | Target core cell placement density from 0.0 to 1.0 (default: 0.4). |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses that this is a multi-stage automated flow, that it runs on OpenROAD, and that it returns area, utilization, wirelength, and timing slack metrics. It also implies mutation/creation of files, but does not mention whether inputs are modified, how long it can take, or whether it writes intermediate files beyond the optional DEF. It is fairly transparent but could disclose time cost and side effects more explicitly.
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?
One compact, front-loaded sentence that lists the stages, the input type, the tool, and the outputs. It earns its place with useful metrics. Minor issue: it crams many stages into a parenthetical, which could be slightly easier to parse, but overall it's efficient.
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 complex 8-parameter tool with no output schema, the description gives a strong high-level picture, names required inputs (gate-level netlist, top module) implicitly, and lists return metrics. It lacks details on side effects, runtime expectations, and whether it uses SDC or clock period, but the schema fills parameter gaps and the sibling list provides alternative-stage context. Mostly complete, with minor 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 100%, so the baseline is 3. The description does not add semantics beyond the schema because it only summarizes the overall flow and outputs, not the individual parameters like netlist_file, top_module, or core_utilization. The schema already documents each parameter well.
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 is a specific verb+resource statement: it performs end-to-end automated digital ASIC physical design (floorplanning, placement, routing, and static timing analysis) on a gate-level netlist using OpenROAD, and names the exact metrics returned (area, utilization, wirelength, timing slack). This clearly distinguishes it from the sibling tools, which each handle a narrower stage (floorplan, place, route, sta).
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 the tool is for full physical design flow and returns metrics, and the sibling list makes alternatives explicit. However, it does not explicitly state when to use this end-to-end tool versus calling the individual stages (openroad_floorplan/openroad_place/openroad_route/openroad_sta). The guidance is clear contextually but lacks a direct 'use this instead of...' statement.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
openroad_routeA
Performs global routing (FastRoute) and detailed routing on a placed DEF file, reporting wirelength and DRC violation metrics.
| Name | Required | Description | Default |
|---|---|---|---|
| cwd | No | Optional working directory. | |
| output_def | No | Output routed DEF file path. | |
| placed_def | Yes | Placed DEF file path. | |
| timeout_ms | No | Timeout in milliseconds. | |
| top_module | Yes | Name of the top-level module. |
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 the core behavior (routing and reporting metrics) but does not mention side effects like writing the output DEF, output format details, or error behavior. Some transparency is present, but significant gaps remain.
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?
A single sentence that states the core action, the algorithm, the input, and the outputs without any fluff. Information is front-loaded and easy to parse.
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?
With no output schema and no annotations, the description should explain what the agent can expect in return. While it mentions reporting metrics, it does not specify the output format or whether files are written. For a 5-param tool in a suite, this is adequate but not fully 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 100%, so the schema already documents all parameters. The description adds contextual value by clarifying that routing operates on a placed DEF and reports metrics, but it does not add detail beyond the schema for individual 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 a specific action: performing global routing (FastRoute) and detailed routing on a placed DEF file. It also names the resource and the reported outcomes (wirelength and DRC metrics), which distinguishes it from sibling tools like openroad_place and openroad_sta.
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 phrase 'placed DEF file' implies the tool is used after placement, but there is no explicit guidance about when to choose this tool over siblings such as openroad_pnr or openroad_place. No alternatives or exclusions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
openroad_staA
Performs static timing analysis using OpenSTA on placed or routed DEF files, reporting Worst Negative Slack (WNS), Total Negative Slack (TNS), and critical paths.
| Name | Required | Description | Default |
|---|---|---|---|
| cwd | No | Optional working directory. | |
| def_file | Yes | DEF file path (placed or routed). | |
| sdc_file | No | Optional SDC timing constraints file path. | |
| timeout_ms | No | Timeout in milliseconds. | |
| top_module | Yes | Name of the top-level module. | |
| clock_period_ns | No | Target clock period in ns (default: 1.0). |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations present, the description carries the full burden of behavioral disclosure. It does reveal the core behavior—running OpenSTA and reporting timing metrics—but does not mention side effects, whether it is strictly read-only, how constraints are derived when sdc_file is absent, or the exact form of the report. This is adequate but leaves meaningful gaps.
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 front-loaded sentence with no filler. It packs the tool's purpose, input phase, engine, and key outputs into a compact form that is easy to parse quickly.
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 essential purpose and outputs, but given no annotations and no output schema, it should provide a bit more context. Notably absent is guidance on how sdc_file and clock_period_ns interact, whether the tool writes any files, and what the returned report looks like. The schema covers parameters well, but the overall invocation context is only minimally 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 100%, so baseline is 3. The tool description repeats the placed/routed DEF detail already present in the def_file schema description and adds no new meaning for top_module, sdc_file, clock_period_ns, cwd, or timeout_ms. It neither harms nor meaningfully enhances parameter understanding.
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 a specific verb ('Performs'), resource ('placed or routed DEF files'), and engine ('OpenSTA'), and lists concrete outputs (WNS, TNS, critical paths). This makes it easy to distinguish from sibling flow tools like openroad_place, openroad_route, and openroad_floorplan.
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 establishes the correct context: this tool is for static timing analysis on placed or routed DEF files, implying it is used after placement/routing rather than at floorplan time. It does not explicitly name alternatives or say when not to use the tool, but the usage context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
openroad_toolchain_infoA
Returns active container/host runtime and version information for OpenROAD, OpenSTA, and supported platform PDKs.
| Name | Required | Description | Default |
|---|---|---|---|
| cwd | No | Optional workspace directory. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral disclosure burden. It clearly signals a read-only, side-effect-free operation by saying 'Returns ... information'. It also specifies the scope of what is returned, which is sufficient for a simple info tool, though it does not detail output structure 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 a single, well-structured sentence that front-loads the action and clearly lists the information domains. There is no redundant wording or unnecessary detail.
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, optional-parameter info tool, the description provides enough context: it states what is returned and for which components. There is no output schema, so a slightly more explicit note about the exact return shape would improve completeness, but the current description is adequate for an agent to decide to invoke it.
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 only parameter, cwd, is already fully described in the schema as 'Optional workspace directory', so schema coverage is 100%. The tool description adds no additional meaning about how cwd affects the returned information, but the schema already provides adequate semantics for this optional parameter.
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 ('Returns') and names the exact resource: runtime and version information for OpenROAD, OpenSTA, and supported PDKs. This clearly distinguishes it from the sibling execution tools like openroad_pnr and openroad_sta, which perform operations rather than reporting environment info.
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 the tool is for checking the active toolchain environment, but it does not explicitly state when to use it versus siblings or when not to use it. An agent can infer usage from the info-returning nature, but there is no direct guidance or exclusion.
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.
6 tool updates
v0.1.0- First observed
openroad_floorplan - First observed
openroad_place - First observed
openroad_pnr - First observed
openroad_route - First observed
openroad_sta - First observed
openroad_toolchain_info
TDQS
Each tool targets a distinct, non-overlapping stage of the ASIC physical design flow: floorplan, place, route, static timing analysis, or the full end-to-end PNR run. The info tool is clearly separated as a utility for runtime details. No ambiguity in purpose.
All tools follow a consistent 'openroad_' prefix with a lowercase action or stage identifier (pnr, floorplan, place, route, sta, toolchain_info). This creates a predictable and readable pattern that makes tool selection straightforward.
Six tools is well-scoped for a physical-design-oriented MCP server covering the main flow stages plus an end-to-end wrapper and an info utility. Each tool earns its place, supporting both granular control and a one-shot option.
The set covers the primary stages (floorplan, place, route, STA) and an end-to-end PNR path, which likely includes clock tree synthesis internally. A minor gap is the lack of a dedicated clock tree synthesis tool for users who need to run CTS in isolation, but the core lifecycle is otherwise complete.
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Connectors
Protocol-native energy infrastructure orchestration for AI data centers. Provides 46 MCP tools across 8 grid protocols (IEC-61850, DNP3, Modbus, OCPP, OpenADR, IEEE 2030.5, IEC 60870-5-104, ICCP) with 5 core API primitives: connect, dispatch, settle, comply, and intel. Enables AI agents to programmatically interact with substations, grid interfaces, and energy assets for real-time workload-grid coordination.
Run, build, and validate firmware on virtual hardware from your AI agent. Hardware knowledge corpus.
AI-native git hosting — repos, PRs, issues, CI gates, and AI code review over MCP (60 tools).
Code intelligence platform for AI agents. 20 tools for architecture, security & impact analysis.
Related MCP Servers
- FlicenseAqualityFmaintenanceA comprehensive Model Context Protocol server that connects AI assistants to Electronic Design Automation tools, enabling Verilog synthesis, simulation, ASIC design flows, and waveform analysis through natural language interaction.6108-
- FlicenseAqualityDmaintenanceEnables AI assistants to perform Electronic Design Automation (EDA) tasks including Verilog synthesis, simulation, ASIC design flows, and waveform analysis through a unified interface.6-
- AlicenseNot gradedqualityCmaintenanceEnables AI assistants to drive Xilinx Vivado, Intel Quartus, and Anlogic TangDynasty for FPGA development, including project creation, synthesis, implementation, timing closure, and hardware programming through natural language.MIT
- FlicenseAqualityCmaintenanceEnables AI coding agents and IDEs to lint, compile, syntax-check, and simulate Verilog/SystemVerilog designs through structured, token-efficient MCP tools with isolated containerized toolchains.4-
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/zesun33/mcp-openroad'
If you have feedback or need assistance with the MCP directory API, please join our Discord server